Weather Forecasting

Weather forecasting is the use of science and technology to forecast atmospheric conditions for a certain place and period. For centuries, people have tried to forecast the weather informally, and officially since the nineteenth century. Weather forecasting, which used to be done by hand and was focused mostly on variations in barometric pressure, existing weather patterns, and sky state or cloud cover, is now done using computer-based models that account for a variety of atmospheric variables. Weather predictions are created by gathering objective data about the actual condition of the atmosphere at a certain location and using meteorology to predict how the weather will behave in the future. Human feedback is also required to choose the best possible forecast model on which to base the forecast. Weather forecasting is a part of the economy; for example, the United States spent $5.1 billion on weather forecasting in 2009, with gains expected to be six times that amount. Since we know the weather forecast, let us take a look at the importance of weather forecasting pdf and the different methods used to forecast.

Importance of Weather Forecasting

There are various uses of weather forecasting in day-to-day life, it can be as simple as deciding whether to take an umbrella with you on your work or to deciding your outfit. Following are some of the places where weather forecasting plays a major role:

1. Seasons and nature play a major role in agriculture and farming. When it comes to the farming of various fruits, vegetables, and pulses, temperature is extremely important. Farmers didn't have a better understanding of weather forecasts before, so they had to rely on estimates to do their jobs. They do, however, sometimes suffer losses as a result of inaccurate weather forecasts. Farmers will now get all of their forecasts on their smartphones, thanks to advances in technology and the use of unique weather forecasting mechanisms. Of course, education in this area is critical, but the majority of the farmer community at this point understands the fundamentals, making it simple for them to use the features.

2. It aids food grain transportation and storage.

3. It aids in the handling of cultural operations such as harrowing, hoeing, etc.

4. It aids in the implementation of livestock protection initiatives.

5. Weather Forecasting is crucial since it helps to determine future climate changes. With the use of latitude, we can determine the probability of snow and hail reaching the surface. We are able to identify the thermal energy from the sun that is exposed to a region. Climatology is the scientific study of climates, which in simple words mean weather conditions over a period. A bunch of studies within atmospheric sciences also takes the help of the variables and averages of short-term and long-term weather conditions accumulated. Climatology is different from meteorology and can be divided into further areas of study. Different approaches to this segment can be taken. Currently, our primary research goal is to motivate and help the development of efficient and effective measures of Environmental activities.

Types of Weather Forecasting

• Short Range Forecasting: This forecasting will last 1-2 days.

The weather has an immense influence on human daily patterns, the production of food, and personal comfort zones. 

Forecasting plays an important role in planning current and future activities. So, there are other aspects that may have a huge impact on the forecasting outcome. 

However, accurate forecasting is very crucial. Forecasting is an important tool for various analyses. ECMWF is the most precise global model. ECMWF performs way better than the GFS. 

• Medium Range Forecasting: This kind of forecasting lasts 3-4 days to 2 weeks. Medium-term forecasts are made for small strategic resolutions in correlation with the nature of the business. They are very important in the area of business budgeting and development and it is from this forecast that company budgets are decided. inaccurate forecasting can have serious impacts on the rest of the organization, the organization will be forced to be with the unsold stock and will have to overspend on production again. A huge amount of money has to be paid to banks and creditors, and stock may have to be sold at a very less price. Organizations can go bankrupt due to insufficient attention on medium-term sales forecasting. The time period for a medium-term forecast is usually one year.

• Long-Range Forecasts: This forecasting is for times longer than four weeks. Long-term forecasts are for mainly major upcoming strategic decisions to be taken within an organization and for the organization, They focus very much on how to use resources in an optimum manner. They deal with basic items rather than specific items. And therefore, organizations are concerned more with general ongoing trends, following these trends, regular attempts to predict revenue-generating sales over periods greater than two years. In some strategies, For huge industries, accurate predictions might be needed for a decade or more to tackle the changes. The disadvantage of such forecasts is that they cannot be more than unclear. Prediction planners blame the forecast when things go wrong totally opposite what was predicted and forecasting hence receives criticism from all who are impacted. 

Methods Used to Find the Weather Forecasting

1. Synoptic Method:  A systematic study of recent weather forecasts from a wide area is used in this method of weather forecasting. Present weather conditions are linked to comparable scenarios in the past, and predictions are based on the premise that the current scenario would behave similarly to the analogous situation in the past.

2. Statistical Method: Regression equations or other advanced relationships are formed between various weather elements and the subsequent climate in this method of weather forecasting. Predictions or weather criteria are usually chosen based on a potential physical interaction with the predictions.

3. Numerical Weather Prediction Techniques: Numerical weather prediction definition states that it forecasts weather using statistical models of the atmosphere and oceans dependent on current weather conditions. The action of the atmosphere is expressed in this system by a series of equations based on physical laws governing airflow, air pressure, and other data. The method has been shown to be optimal for medium-term forecasts.

Weather Forecasting Process

A weather forecast is made up of three steps: observation and analysis, extrapolation to determine the state of the atmosphere in the future, and estimation of specific variables. One method of qualitative extrapolation is to conclude the weather features will continue to travel in the same direction as they have been.

Observation and Analysis

1. While data-access policies differ by country, all of these reports are sent to regional and global centers through the World Meteorological Organization's (WMO) Global Telecommunications System (GTS).

2. The data is then compiled, redistributed in the GTS, and used in various numerical forecasting models. Typically, these numerical models begin with data collected between the hours of 0000 and 1200 UTC (7 A.M. and 7 P.M. Eastern Standard Time, respectively).

3. To aid the forecaster, the data is printed, mapped, and graphed in several ways. Furthermore, some "initialization" routines slightly change the data when it enters a prediction model only for that model.

Extrapolation

1. The degree of approximation to the equations varies greatly between models. Since more computing time is taken to do the work, the more precise the approximation, the more expensive the model is to use.

2. In the United States, forecast-model research is centralized at the National Centers for Environmental Prediction (NCEP) of the National Weather Service in Suitland, Maryland. There, a cutting-edge supercomputer is tasked with operating four primary models. Two of the styles are concerned with North America and its environs. The other two versions surround the entire globe in a standardized manner. Each domain has a basic model that is intended for fast computation as an early update even though machine problems occur. For each domain, the other model is more comprehensive, giving a better solution at a higher cost.

Estimation

1. When a forecaster sets out to estimate a particular variable, such as the minimum temperature on a given night in the city where he or she is based, he or she has access to a wealth of observed and model-generated evidence. However, none of the data can be used to make a concrete prediction.

2. In the current scenario, the forecaster must also apply knowledge of average climatic conditions, local microclimate fluctuations, and standard model behavior. The NWS has made significant efforts to express this kind of additional data using statistical regression equations. The coefficients in these equations differ depending on the geographical area and season.

History

People have attempted to predict the weather for centuries. The Babylonians used cloud formations and astrology to forecast conditions in 650 BCE. Aristotle's Meteorologica, written about 350 BCE, identified weather patterns. Theophrastus also compiled the Book of Signs, a book on weather forecasts. Weather prediction lore in China dates back to at least 300 BCE, around the same period as ancient Indian astronomy developed weather-prediction methods. Observed cycles of events, also known as pattern recognition, is used in ancient weather forecasting methods. It has been noted, for example, that if the sunset was especially red, the next day was usually sunny. This knowledge was passed down over the years, resulting in weather lore. However, not all of these forecasts are accurate, and many of them have been proved to be unreliable after being subjected to stringent statistical research.

Did You Know?

1. A cricket's chirps can be used to determine the temperature.

2. -89.2°C was the coldest temperature ever officially reported.

3. A "BUST" is a term for getting the forecast wrong.

4. Sandstorms can overwhelm entire cities.

5. Dogs and cats have the ability to sense when a tornado is coming and then they act accordingly. 

6. In 1684, The River Thames was solid frozen for two months. 

7. It was so cold in the year 1899, that the Mississippi River froze over its complete length.

8. In December 1811, an earthquake caused a few parts of the Mississippi River to flow backward.

9. In 350 BC, Aristotle studied and wrote about Meteorology.   

10. Aomori, Japan is the snowiest city on Earth with an average of eight meters of snow each year.

11. U.S. roads use More than 22 million tons of salt every winter. 

12. Studies show that some tornadoes were faster than formula one racing cars.