Weather satellites provide meteorologists with the data they need to make accurate, life-saving forecasts. These satellites continuously orbit above us, providing atmospheric observations that are ingested into numerical weather prediction (NWP) computer models.
Environmental satellites also have imaging capabilities that allow meteorologists to watch storms develop from space, enabling them to identify volcanic ash and smoke from wildfires.
Satellite imagery is an essential part of the weather forecast process. It provides meteorologists with a snapshot of current conditions, which they can use to run highly complex calculations to forecast what the atmosphere will do next. Meteorologists use this information in their weather models, such as the US Global Forecast System (GFS) or the European Centre for Medium-Range Weather Forecasts (ECMWF).
There are three main types of satellite images used by meteorologists: visible imagery, infrared imagery, and water vapor imagery. Each type of image is used for a different purpose.
VIS IMAGERY: The first type of satellite imagery is based on sunlight, which is reflected off clouds and other objects. This is why it’s able to detect the thickest clouds, such as cumulonimbus (thunderstorm) clouds, which are white on the VIS satellite image. Clouds that reflect less light, such as cirrus clouds, will appear gray on the VIS satellite picture.
Another useful type of imagery is infrared, which measures heat radiating off clouds. These images are especially useful for determining thunderstorm intensity and identifying fog and low clouds.
However, these images don’t work well for detecting large hail or tornadoes. In these cases, satellites need to have a larger area of coverage. This isn’t possible on most satellites.
These images also require specialized software to interpret them. This makes them more expensive than other methods of weather forecasting, but it allows for a greater level of detail.
Infrared satellite images have a wider field of view and allow meteorologists to see more detailed information, including the surface of the Earth. This is useful for identifying terrain features such as lakes or rivers that are not visible on other kinds of satellite imagery.
The IR images are not as useful for identifying clouds, but they can provide useful information about the temperature of the Earth’s surface. The satellites that collect this kind of data are called “Earth Resource Observation Satellites” or “EROS” and they are lightweight, low-earth orbiting, high-resolution satellites designed for fast maneuvering between imaging targets.
EROS satellites are mainly used for national and commercial applications, such as mapping, border control, infrastructure planning, agriculture, environmental monitoring, disaster response, training and simulations. Other uses of EROS satellites include anomaly hunting, which involves searching for unexplained phenomena that can’t be explained by other types of data.
Weather observations are one of the most important factors in enabling accurate and timely weather forecasts. They are used to initialize conditions fed into numerical weather models, providing essential data that can be incorporated into short- and long-range forecasts.
These observations are made by a variety of sensors that are sent to the Earth from orbit. They measure reflected and infrared light and measure the temperature and humidity of the atmosphere. This information is then digitized and turned into images for use by weather forecasters.
The most common observations include cloud cover, precipitation, and lightning. Many other types of measurements are also taken by different types of instruments, such as radars and soundings.
Observations can also be used to verify the accuracy of weather forecasts. These can be made from a variety of data sources, including radars and weather satellites.
Weather observation data is collected by hundreds of manned and automatic surface stations, a network of upper-air stations, ships, radars, and aircraft that are equipped to make specialized measurements. They record temperature, pressure, moisture, wind speed and direction, clouds and precipitation, and a few other parameters.
Climate data is also collected by a range of meteorological and oceanographic satellites. These satellites are located in geostationary and polar orbits and provide global, detailed observations of the atmosphere, land and oceans for meteorological, climate monitoring, and other applications.
These observations are essential to the scientific study of climate and weather and have played an important role in the development of atmospheric predictability on time scales from hours to months. They are especially useful for the detection of fast-developing severe weather (nowcasting) and to monitor atmospheric and oceanic processes.
These observations are also critical to the development of reanalysis production systems. These systems, such as ECMWF’s CAMS system, use a range of observations to assimilate the data from atmospheric models and produce accurate forecasts.
Satellites provide a “bird’s eye view” of the atmosphere that meteorologists use to help predict everything from hurricanes and tornadoes to the amount of snowfall at ski resorts. The observations they make are ingested into computer models and used to forecast the weather in ways that would be impossible without them.
Models are highly complex computer programs that take current weather observations, create snapshots of the atmosphere, and run equations to predict what will happen next. This is done for any time in the future from an hour to ten days and even months ahead.
In order for these models to function, the atmospheric data they need must be gathered in large quantities. This is made possible through the use of environmental satellites, which orbit above us constantly and gather atmospheric observational data as they fly by.
To get this information, environmental satellites send a variety of instruments up into the atmosphere. These instruments collect information about the temperature, pressure, and water vapour in different areas of the atmosphere.
These measurements are then analyzed and interpreted by meteorologists. These results are then used to guide the computer modeling process. These computer models are called Numerical Weather Prediction (NWP) models.
NWP models like the United States’ Global Forecast System (GFS) and Europe’s Centre for Medium-Range Weather Forecasts (ECMWF) use the information from these atmospheric observations to create a simulation of the current atmosphere. The simulated radiances from these models then provide an accurate snapshot of the atmospheric state that the computer model needs to operate.
Once the model is completed, it will produce outputs, which are based on the equations derived from the atmospheric data, at grid points throughout the atmosphere. These outputs, if correct, will specify the predicted weather at various future times over an area covered by the grid points.
The forecast model is then merged with observations to produce weather forecasts in real-time. This is called data assimilation. The outputs from these two processes are then incorporated into a single global weather prediction model, known as the Climate Analysis and Modeling System (CAMS).
Data assimilation is an important step in the NWP modeling process that helps to improve the accuracy of weather forecasts by pulling together the best possible data with the most accurate modeling. It is also an important step in the climate monitoring and climate research process.
Weather forecasting is the process of gathering and analyzing data about the Earth’s atmosphere to predict the weather for a specific time period. Weather forecasts are used for a variety of purposes, including air travel, agriculture, and business operations.
There are different types of weather forecasts, ranging from short-term to long-term. The short-term forecasts are used for a few hours ahead, while long-term forecasts are for several months to 2 years into the future.
The short-term forecasts are usually made by a meteorologist or another professional who uses a computer to calculate the information. The forecasts can be very accurate and can help you make the right decisions about your plans for the day.
Some of these forecasts include a series of satellite images and some additional information such as wind speeds and directions or pressure patterns. This can provide an instantaneous picture of the weather, allowing you to decide what type of activities are possible, and if you need to prepare for stormy weather or not.
These images also help you to determine how much rainfall you will get. Some of these forecasts will even tell you if the weather is likely to get colder or warmer than usual.
Using these satellite images to forecast the weather is becoming more commonplace as we learn more about how to use them effectively. The main thing is to understand what you’re looking at, how it can affect your plans, and how to interpret the information so that you can make informed decisions.
The next step is to create a model of the atmosphere. The weather model is a computer program that takes in all the information about the atmosphere and makes predictions of what will happen in the future.
There are a number of different models for different aspects of the atmosphere. These include global, regional, and mesoscale models.
These models are based on observations from various sources, including radar, satellites, and weather stations. These are then combined and analyzed through methods such as data assimilation and objective analysis. The model is then adjusted and recomputed to create a new forecast.