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        The main goal of weather forecasting is to provide information to the public so informed life or business decisions can be made. This could range from using sunscreen when going out or getting prepared for severe weather entering the area. To provide this support, forecasters have to look through a myriad of different maps and charts all providing different information to create an effective forecast. Maps can range from satellite imagery, surface pressure maps, or numerical modeling. Forecasters must choose which information is best applicable to the situation involved. For example, an area under a high-pressure system could expect calmer conditions, so looking at an Energy Helicity Index map wouldn't be applicable. To do this, forecasters can use a concept called a forecast tunnel to create a forecast. This process describes how meteorologists can start from the top of the atmosphere  to the surface to develop a succinct forecast.

        Planetary and Hemispheric scales start this process and this could involve parameters like Rossby Waves. They are on the scale of tens of thousands of kilometers, in respect of size of the system. Afterward, you move to the synoptic-scale which is on the scale of several hundred to several thousand kilometers. This would typically involve features like high and low-pressure systems. Lastly, the smallest scale for the forecast tunnel is mesoscale. These are smaller-scale features on the order of a few to several hundred kilometers. An example of these features would be sea breeze and squall lines. These scales are interconnected and using the forecast tunnel helps forecasters see these features and how they relate dynamically. 
            
         Furthermore, it is imperative that meteorologists make forecasts promptly so that the forecast remains relevant to the public. Traditionally, the larger the scale, the fewer time forecasters will spend working on the specific features within that time scale. Planetary scale features are on such a large magnitude that they shouldn’t experience significant changes during a traditional forecast period, so monitoring it should take the least amount of time. Conversely, mesoscale features require more time because the nature of the size scale is smaller. These features are harder to examine if they are going to impact the forecast area and how they will evolve with time. 

Photo Creds: The Comet Program

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©2020 Weather Forecaster Dakari Anderson

   Photo Credit: New York Times

             It’s well known that acid rain causes damage to plant and animal life. When acid rain flows through an environment, it can break down aluminum from its surroundings in the soil and carry the metal with it, consequentially, lowering the pH of the water nearby and underground. Both effects can cause a great deal of damage to plant and animal life by making the water intolerable to certain species. Since plants and animals are interconnected by food chains, animals resistant to pH changes are adversely affected when their food supply consumes their own tainted food supply. For example, many plants may die in an area due to acid rain, causing an herbivore that can withstand the pH changes to die as well because its source of food is gone.

            What’s not as well known is how exactly acid rain originates. Most of it comes from harmful pollutants made by humans, especially those from burning fuel in factories or cars. When fuel is burned, it releases energy as well as byproducts including carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxides (NOx). By observation, one can tell that water mixes well with a lot of compounds. The water in the atmosphere is no exception. When water in the atmosphere meets these byproducts, they can mix and create potentially hazardous compounds such as carbonic acid (H2CO3), sulfuric acid (H2SO4), or even nitric acid (HNO3). While these compounds are greatly distilled by the water, they are still harmful to plant and animal life. Additionally, gases from burning fuels don’t even have to mix with rain to reach the ground. They can sink into the ground in their original forms and stick to objects near the surface, adding to the adverse effects from gas pollutants.
           
         Since carbon dioxide is a relatively abundant trace gas in the atmosphere, virtually all rainwater is at least slightly acidic because of the presence of carbonic acid. Thankfully, carbonic acid is a weak acid that doesn’t affect the pH of rainwater to the point of making it harmful. The same could not be said for sulfuric acid or nitric acid. These acids are quite powerful in comparison to carbonic acid. They can cause the pH of water to swing down and create acid rain, which has an average pH of 4.3. For comparison, the pH of pure water is 7 and the pH of regular rain is 5.6. It’s important to note that the pH scale is not linear, but logarithmic. That is, it doesn’t increase and decrease at a constant rate. Instead, it increases and decreases exponentially the farther it gets from the neutral pH of 7. As a result, acid rain is over 10 times more acidic than regular rain on average!

          What can be done to prevent acid rain or decrease its impact? The primary answer is to decrease the number of harmful byproducts coming from factories, since it’s not possible to get the gases out of the atmosphere once they’re up there. Many factories have methods of extracting harmful products out of their emissions and international treaties exist to limit certain types of emissions from factories. It’s essential for those who wish to decrease the prevalence of acid rain to understand where it comes from so the sources of these pollutants can be targeted and limited. By having a full comprehension of how acid rain is formed people can work towards limiting their harmful impacts.
           
            © 2020 Weather Forecaster Cole Bristow

Many of us see weather forecasts and hear the terms “European models” and “American models” within them. But do we know what the difference is between these models and what they both mean? The main differences between the two models involve accuracy and time frame of predictions; however, both are global models.

The American model, also known as the Global Forecast System model (GFS), is operated by the National Weather Service (NWS). Forecasts are produced four 4 times a day, and can predict up to 16 days in advance. The computing power used to create these models can process eight 8 quadrillion calculations every second. According to the National Oceanic and Atmospheric Association (NOAA), the computer that runs these calculations is in the top 30 fastest computers in the world.

The European model, known as the European Center for Medium-Range Weather Forecasts (ECMWF), is more powerful than the American model, and generally a better model. The main reasoning for this is the organization and processing of the data, as well as the power of the supercomputer itself. In fact, the European model was able to accurately predict when Hurricane Sandy would turn into the northeastern section of the United States before the American model could. While the American model can predict up to 16 days in advance, the European model can only predict up to 10 days in advance. Although the time frame is shorter, 10 days is typically seen as the “practical limit” of forecasting, and thus is more accurate than the American model. Forecasts are only so reliable, and the farther in advance one wants to forecast, the less accurate a forecast becomes.

©2020 Weather Forecaster Sarah Cobern
To learn more about weather forecasting, visit https://www.globalweatherclimatecenter.com/weather-education

​Sun Halo. Source: https://sites.google.com/site/thebrockeninglory/
 

For sun dogs, we need for there to be refraction off ice crystals at an angle of around 22-24 degrees from the sun in any direction. Depending on where you’re standing and if the conditions are right, you may be able to see the entire sun dog from your field of  vision!