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When meteorologists make forecasts, they rely on many tools. One of these key tools are weather models. There are various weather models to choose from, which each have a different range of dates. These models use not only the current conditions, but also climatology to predict just what will be predicted to happen up to a few weeks out. Since this is based on historical movement of storms and what previous results, the end product may end up being rather off when looking at an event beyond five days away from an event. An example of this just recently happened for people located in the Midwest and some portions of the Southern Great Plains. On the 06 Z run on December 5th, 2019, the GFS, one type of model, predicted that there would be 28 inches of snow that fell in parts of west Tennessee and western Kentucky. This type of snow is not heard of in these parts of the country, so it sent people into a frenzy.  The very next day, the 06 Z run said that around the same time of this event, there would not be any snow for west Tennessee and western Kentucky. If anything were to fall, then it would only be a trace amount at the most.  So here’s the question: why do two model runs differ so much over the course of 24 hours? This can factor greatly because of the data that is put into a model can vary, and if someone puts in bad data, then a bad model run will occur. Even the best meteorologists make mistakes, so if someone else does not catch that mistake, then the end product will not only be wrong this far out, but for the near future as well.
Another factor that leads to differing results would be related to the historical tracks of storms and climatology. If a storm takes a certain path around the same time of the year, then any model that attempts to forecast beyond five days will rely on what has happened in the past. Much of the knowledge that deals with weather came from noticing that these patterns brought this type of weather over and over again. So if it happened once, then there’s always a chance of it happening once more. Models tend to rely on the calculated pattern that the occurrence will happen again each time they forecast this far out because the data only predicts the weather a few days out, not weeks in advance. With this example, both of these models were predicting an event that was over a week and a half away, so the forecast from this far out cannot be fairly relied on. However, many people see a forecast like the first model and worry about what will happen. In the next part of this series, there will be some tips that forecasters use to establish a hypothesis of what could happen in the future. For more information on other tools used to make forecasts, make sure to check out www.globalweatherclimatecenter.com/weather-observations! ©2019 Weather Forecaster Shannon Sullivan (Source: College DuPage GFS Model Runs)
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Forecasting weather over the ocean presents a unique challenge due to the lack of ground observations that can survey the area. Buoys and ships can give data that can help with forecasts and warnings. However, these are sparse and cannot effectively cover the entirety of the ocean. Satellites help mitigate this with the use of scatterometers and altimeters. We use altimeters to retrieve significant wave heights and wind speed, and scatterometers provide information about wind speed and direction. Both are satellite microwave radars, and they send energy towards the ocean’s surface, measuring the energy that returns to the satellite. They fly on Low Earth Orbiting (LEO) satellite and provide global coverage, flying over the same location twice in a single day, with more frequent observations closer to the poles. Specifically, altimeters can help measure significant wave heights over the ocean. The National Weather Service defines this as the average of the highest one-third (33%) of waves (measured from trough to crest) that occur in a given period. When there are waves present, the return pulse takes a longer time to reach the satellite and changes the shape of the pulse. Using this, the altimeter can measure the wave height at a spacing of 7 km over the ocean’s surface. Significant wave height could have impacts on coastal erosion and ships attempting to avoid dangerous waters. Scatterometers work similarly by sending a pulse towards the ocean surface and measuring the energy received by the instrument. They use the Bragg Scattering principle where scatterometers send a pulse with a similar wavelength of tiny ripples embedded within the ocean’s wave. This causes a resonance that causes energy to be scattered towards the satellite. This allows scatterometers to measure wind speed and direction. Scatterometers measure at a particular angle called an incident angle to allow it to accurately measure radar backscatter. Radar is most sensitive to wind speeds for incidence angles between 30° and 60°. Having an angle outside this range would cause the satellite to miss the radar backscattering. Also, to get wind direction, scatterometers must view the embedded waves from different horizontal directions. This allows for it to narrow down the possible directions given a particular wind speed.  There are a few hindrances behind altimeter and scatterometer readings. Rain can be detrimental to observations as rain can absorb the initial radar pulse lowering wind speed measurements and can scatter energy back to the satellite which would overestimate wind speeds. These effects are significant because when there is heavier rain the measurements would be more sensitive to the rain’s effects. Altimeters and scatterometers provide a great resource in monitoring significant wave heights and wind speed/direction estimates. This can help in marine forecasting, aiding ships in where to travel, monitoring weather over the ocean such as high and low centers of pressure, and coastal warnings regarding significant wave heights and the threats that come with it. If you are interested in satellites and other weather obervances, be sure to click here to learn more about it. Photo Credit: The Comet Program ©2019 Weather Forecaster Dakari Anderson Revisiting how and why GOES-East is a true revolution in atmospheric satellite observations.10/27/2019   DISCUSSION: As we continue to move through the remainder of 2019, millions of people spread around the world have already enjoyed the magnificence of the advanced remote sensing capabilities since late November 2016. It goes without saying that GOES-East has forever changed the way we consider and study a good portion of the Western Hemisphere. From studying severe weather events, to considering the impacts from wildfires, to major flooding events, to tropical cyclones from around the world, GOES-East has completely changed the ways in which we study and forecast high-impact atmospheric phenomena. More specifically, forecast accuracy and overall reliability have collectively increased over time in most cases. This is due in part to the vastly increased resolution of this and other recent satellite imagers having the ability to enable atmospheric forecasters and research scientists to better anticipate how and why certain events may unfold.
In looking a little closer, GOES-East has allowed such advances as more accurately being able to anticipate severe storm initiation ahead of a major severe weather outbreak which consequently allows for longer average lead times for storm watches and/or warnings on a regional-to-local scale. In addition, GOES-East and earth-orbiting imagers have enabled tropical forecasters to get way better insights into the early as well as the critically-important development stages of tropical cyclones across the tropical Atlantic Ocean basin and beyond. One such example from right here in 2019 would be the critical application of GOES-East into the early-on longer-term and then the latter critical shorter-term forecasts issued by the NOAA NWS National Hurricane Center for Hurricane Dorian which has momentously gone down in the history books as one of the most powerful and prolific tropical cyclones of all-time across the tropical Atlantic basin. In the brief high-resolution visible satellite imagery attached above, you can just begin to appreciate and respect the incredibly high-level of tremendous detail which was provided by the state-of-the-art capabilities from GOES-East. You can see the gravity wave action emanating from center of the storm and moving outward, the symmetry transverse banding features on the periphery of Dorian’s circulation, and even the mesovortices located within the eye of Dorian as the storm was approaching the far eastern Bahamas. These were collectively a major indication of a powerful and dangerous storm and helped to verify the major importance of as many people as possible to respect the inherent dangers associated with this incoming tropical cyclone. Moreover, it is imperative to point out that this is just one of literally hundreds of instances in which GOES-East and similar satellite imaging platforms have forever changed the ways in which the global geoscience community considers and studies the atmosphere. To learn more about other weather observational topics from around the world, be sure to click here! ©2019 Meteorologist Jordan Rabinowitz The Global Forecasting System model officially becomes updated (Photo Credit: Tropical Tidbits)6/26/2019  DISCUSSION: In June 2019, the National Centers for Environmental Prediction (NCEP) announced that the Global Forecasting System (GFS) model has been successfully updated. The NCEP is the agency in the National Weather Service (NWS) that handles predictions for aviation, hurricanes, severe storms, oceans, and even space weather. The NCEP also is in charge of several of the models that are used by meteorologists such as the GFS, the North American Model (NAM), and the High Resolution Rapid Refresh (HRRR) model.
These models are used by meteorologists in the private sector as well as by networks to aid with making forecasts. The usage is based on the various model resolutions as NAM and HRRR are regional models with lower resolutions at 12 km and 3 km respectively while the GFS has a bigger resolution as it is a global model. The resolution is a key factor as lower resolution models factor in local topography and convective activity such as thunderstorms and cumulus clouds. In addition, another component is the capability on how far the models forecast, as the HRRR only forecasts for 18 hours, the NAM forecast for 84 hours, and the GFS goes for 384 hours which would help give a bit of an indication down the road especially for the hurricane track cone. However, the models would be less accurate the further out the forecast Is, especially the GFS in it’s 384 hour time period, due to different conditions such as topography, biases in temperature and winds, and events such as snow on the ground and smoke from a fire would play a factor that would change gradually every timestep. The new update for the GFS includes a change in the dynamic core. The dynamic core is the engine of the model which takes in equations related to atmospheric movements such as the water cycle or the solar heating. The new core that is being implemented is called the Finite Volume Cubed-Sphere dynamical core (FV3) and among the features of the GFS-FV3 is the ability to simulate the atmosphere in hydrostatic and non-hydrostatic conditions. Hydrostatic conditions indicate that there is constant mass and constant pressure throughout the surface of a fluid such as the atmosphere. The updated GFS-FV3 model was tested for over a year to fix any technical bugs. Among the test cases of the GFS-FV3 was Hurricane Florence as well as the January 2018 blizzard in the Northeast. The results of the two test cases were that the GFS-FV3 was performing much better than the old version of the GFS such as being closer to the actual precipitation amount in the case of the blizzard as well as having tracked Florence more accurately. The GFS-FV3 also is more efficient and faster than the legacy GFS on the computers at NCEP and in general. The legacy version of the GFS will continue to be functional until September of 2019 in order to help resolve some issues of the GFS-FV3 as well as to provide data to users such as researchers and forecasters. The GFS-FV3 is already available to the public on some weather model websites. The GFS-FV3 will become a topic of many talks at upcoming American Meteorological Society (AMS) and National Weather Association (NWA) conferences in the next few years regarding its performance. To learn more about other interesting weather observation-based stories from around the world, be sure to click here! © 2019 Meteorologist JP Kalb 
DISCUSSION: When it comes to understanding the atmosphere, it is first important to understand that it is far from simple regardless of what situation is at hand. Particularly in the middle to upper portions of the atmosphere of Earth, there is a substantial degree of unique complexity at hand. This is because in the middle to upper parts of the atmosphere there is a lot of complicated interaction between various atmospheric features such as low-level jets (which provide added moisture and atmospheric instability to various regions) and jet streams (e.g., the subtropical jet stream and the polar jet stream). It often will work out such that you need the perfect “mixture” of low, middle, and upper-level atmospheric components to come together in order to form a near-perfect to perfect storm.
As we look back to March of 2019, it was quite easy to find a situation in which there was a truly classic and complicated interaction of jet streams. More specifically, it was the classic Plains blizzard which formed back on March 13th, 2019 which exhibited a unique and complex interaction between the subtropical and polar jet streams which allowed for a period of rapid intensification to unfold with the mid-latitude low-pressure system which severely impacted the central Plains states back in March. As we take a closer look at the factors which came together to allow for such a powerful system, you can see in the graphic attached above (courtesy of the Meteorologist Stu Ostro from The Weather Channel) that there were two disturbances contained within the respective jet stream features noted above which helped to facilitate the development of this powerful and historic Plains blizzard. These respective disturbances within the respective jet streams which combined to help form this truly historic blizzard and highlighted in blue and you can see how they merged to then form this powerful low-pressure system. To learn more about other interesting weather observation-based stories from around the world, be sure to click here! © 2019 Meteorologist Jordan Rabinowitz 
DISCUSSION: There is absolutely no debate that Tropical Cyclone Fani’s recent period of robust intensification ahead of its landfall in eastern India “turned many heads.” In the days leading up to its eventual landfall, Tropical Cyclone Fani was not all that organized and symmetric which is a key aspect of tropical cyclones which one would typically look for when it comes to an intensifying or a rapidly intensifying system. Having said that, when it comes to observing tropical cyclones in the day leading up to a given landfall, it can be interesting to view a given tropical cyclone from a more global perspective.
One such example of how atmospheric and climate scientists can and will view tropical cyclones and other atmospheric phenomena from around the world is by way of the Global Precipitation Mission (or GPM). The Global Precipitation Mission is a global initiative where several international satellite agencies have come together and joined respective forces to create a global network. This global satellite coverage network operates in such a way that the collective satellites contribute to a global picture of all the atmospheric phenomena from around the world are viewed together. In the brief clip attached above, you can see how over the past 7 days, there was one particular weather event which dominated the global picture over in the Bay of Bengal. That particular event was Tropical Cyclone Fani which appears to fill up most of the Bay of Bengal as it became increasingly more organized with time. If nothing else, this particular tropical cyclone goes to show that even if a given tropical cyclone does not appear to have it “all together”, that is by no means any reason to believe that a storm cannot get itself organized under the right environmental conditions. Moreover, when there is activity of any capacity, it is always imperative to remain aware and fully cognisant of the system’s presence and to never assume anything. To learn more about other weather observational perspectives on higher-impact events occurring around the world, be sure to click here! ©2019 Meteorologist Jordan Rabinowitz 
DISCUSSION: Middle Spring time – a time of the year in which storms become more prominent. With the growth of smartphone use in everyday life, the enhanced ability to report ongoing weather phenomena continues to provide more power to citizens and meteorologists alike. The Meteorological Phenomena Identification Near the Ground (mPING) network, served up by the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma, allows for people to report ongoing precipitation based on the type of precipitation that is falling. A network such as mPING brings together citizens, forecasters, and researchers alike in that much more can be collected about the instantaneous outdoor environment when precipitation is occurring. Reports can arrive to explain different types of precipitation, but the common goal of a network such as mPING is to bring together crowdsourcing of meteorological phenomena to best improve coverage of observations alongside other precipitation detection platforms.
To understand why a network of weather observation reporting such as mPING is essential, it is important to examine the supplementary benefits it can provide along with other types of observations. Most commonly, doppler radars are used to detect hydrometeors like rain, snow, hail, and graupel at various different angles in the atmosphere ranging from 0.5 to 19.5 degrees above the ground reference. Recent advancements to radar technologies such as dual-polarization gives forecasters plenty more information into the horizontal and vertical size and shape of hydrometeors. However, radars cannot detect surface-level hydrometeors and do not always provide a clear and obvious picture as to whether or not precipitation is actually occurring and if so, what type of precipitation is occurring. This is where storm reports and observations play a role in closing the gap between what is observed on radar and what is actually happening on the ground. This is especially helpful for meteorologists in forecast centers where in many cases, there are no windows to the outside, and thus need to rely on external spotters and common folk to report ongoing precipitation. So how do the reports impact researchers and forecasters? The answer lies in the form of verification of the data. Forecasters and researchers can utilize the data coming into the mPING servers and verify against the observations in order to improve data quality and reliability. In addition, observations near the ground can help to enhance weather forecast models such that observations can give forecasters an insight into whether or not a forecast was good or bad, as well as any improvements that can be made to ensure improved forecast skill. Improved forecast skill is always a plus as it gives forecasters more certainty in predicting future precipitation. Ultimately, the mPING network empowers the everyday citizen to make a difference with each report. More information on mPING can be found at the NSSL website here. To learn more about other interesting weather observation topics from around the world, click here! © 2019 Meteorologist Brian Matilla 
DISCUSSION: There is no question that as atmospheric and climate science entered the 21st century, atmospheric observations took on a whole new meaning with a state-of-the-art approach to how and why things are done. One such example to prove this point is regarding the extent to which the GOES-16 satellite imager blew away the atmospheric and climate science community in terms of its unique ability to observe the most recent powerful coastal storm which caught the attention of the Mid-Atlantic and Northeast coastal regions.
A perfect example of how the GOES-16 satellite imager stunned the entire meteorological world was in the context of this satellite’s ability to view the lightning occurring in association with this most recent coastal storm which rapidly intensified just offshore from the North Carolina coastline. More specifically, as GOES-16 watched the system developed both in the vicinity of the coastline and then just offshore from the North Carolina coastline, there was substantial lightning coverage which expanded within and near the center of the system’s core circulation as well as along the progressing cold front. What was most impressive was the extent of the detail which was provided by the GOES-16 Geostationary Lightning Mapper (GLM) imaging platform. What was most impressive was the fact that during the 120-minute footage clip of the GLM in action, there were even some moments where there appeared to be semi-symmetric lightning bursts in the center of the core circulation. This is a phenomenon which is often found in association with near-perfectly symmetric and very intense (and often mature) tropical cyclones. This finding proved that even though this extra-tropical cyclone developed rapidly just offshore from the U.S. East Coast, it did attain radar-based structure in the context of its precipitation which somewhat resembled a hybrid hurricane. This is a finding which is most common to be seen in association with rapidly intensifying low-pressure systems (i.e., in non-tropical situations) since when extra-tropical cyclones rapidly intensify, they can often take on characteristic appearances resembling low-end intensity tropical cyclones from a precipitation-based standpoint as far as regional Doppler radar observations are concerned. This structural resemblance occurs as a result of such rapidly intensifying systems quickly wrapping up and becoming more tightly-wrapped and more powerful low-pressure systems. Thus, this case and point just goes to show that the atmosphere can produce quite impressive displays when the right conditions and circumstances are in place. To learn more about other interesting weather observation topics from around the world, click here! © 2019 Meteorologist Jordan Rabinowitz  Full-circle rainbow viewed from an airplane. Credit: NOAA A rainbow is an atmospheric optical phenomenon that can be seen in the sky right after it rains, when the Sun is shining behind the viewer and there are no clouds blocking the view. Within a rainbow, sunlight is separated into a spectrum of colors that appear to the naked eye after colliding with water droplets within the air. This is why rain is necessary in order to see a rainbow, and the viewer must be in the perfect position in order to spot it. Because the air is less dense than water, when sunlight passes through a water molecule, the sunlight travels slower through water than through air. This causes the light to refract or bend as it slowly passes through the water droplet. As light passes through the water droplet and refracts, it bounces off the inside of the water droplet before exiting the droplet in the same direction in which it first entered. When the sunlight reflects within the water droplet, the light separates into wavelengths, or colors. Thus when this light exits the water droplet it exits in this new spectrum of colors, displaying a rainbow.  Sunlight refracting and reflecting through a water droplet. Credit: Australian Government- Bureau of Meteorology When viewing a rainbow, the colors vary from violet to red. Because violet is the shortest wavelength of visible light, it will appear to bend the most as light exits the water droplet, and therefore can be seen at the bottom of the rainbow. Red is the longest wavelength on the visible light spectrum and bends the least out of all of the colors, and therefore can be seen at the top of the rainbow. The brightness of these colors displayed within a rainbow depend on the size of the water droplets in which the sunlight is refracted. Water droplets with diameters over a few millimeters create bright and vivid colors, while smaller water droplets with diameters less than .01 millimeters create very faint rainbows in which the colors appear almost white and blend together. Rainbows are most common in the summer and are quite rare during the winter because in order to observe a rainbow in the sky there must be both sunshine and rain, therefore water droplets in the air. This is a common occurrence during the summer months. During the winter months, water droplets within clouds are often frozen ice particles that are incapable of scattering sunlight in order to create a rainbow. These frozen ice particles however can sometimes scatter and reflect light into very unique patterns.  Double rainbow in Alaska. Credit: Eric Rolph- CC-BY-SA Double rainbows are a phenomena that may also appear if sunlight is reflected two times within the water droplet before exiting the particle. This secondary rainbow will appear to have the spectrum of colors reversed, with the red wavelength observed on the bottom, and the violet wavelength observed on the top. All rainbows are created through Geometric Optics, by this reflection and refraction of sunlight within a water droplet.
To learn more about other interesting weather observations, be sure to click here! ©2019 Weather Forecaster Christina Talamo  DISCUSSION: On Tuesday, February 12, 2019, the GOES-17 (Geostationary Operational Environmental Satellite) has been declared functional as GOES-West. GOES-17 has taken over the position of GOES-West at 137.2° W for GOES-15 which has shifted to 128° W. GOES-West handles the duties of taking visible and infrared imagery for the Western Hemisphere and the Continental United States. The first system captured by the GOES-17 as the new GOES-West was the atmospheric river event that was forecasted to hit the San Francisco Bay Area on the night of February 12.
GOES-17, however, had some problems after being launched from Cape Canaveral on March 1, 2018. The main source of the issues that arose deal with the cooling and heating systems of the satellite. The cooling and heating of the satellite is vital as the infrared sensors detect radiation mostly in the form of heat from the Earth. The problem with a very warm satellite would make it harder for the infrared sensors to make significant distinctions between temperatures such as between a very cold ground with clear skies and a cloud top. The next satellite in the GOES series to be launched will be GOES-T. GOES-T is scheduled to be launched sometime in June 2020. The GOES-T is scheduled to be used as a storage in orbit just in case one of the other GOES satellites have to go offline or if there is a major malfunction. The GOES-R series, which includes the GOES-17 and GOES-T, is different than the previous GOES satellites as they have more advanced technology including for solar imaging than the GOES-13 series which is the GOES-13, GOES-14, and GOES-15. To learn more about other weather observation topics from around the world, be sure to click here! ©2019 Meteorologist JP Kalb |
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