Growing Advances in Weather Forecasting Technology in 2023

Technological advancements and new techniques are constantly changing weather forecasting. Machine learning, new kinds of sensors, crowdsourcing, and developing better models to predict extreme weather events are some of the emerging trends in weather forecasting.

FREMONT, CA: Meteorology has made enormous progress in the past two decades because of the convergence of multiple factors, including increased processing power, enhanced data modeling, more observational data points spanning from the device in your hand to satellites, and sophisticated data science applications. Providing a precise forecast three to four days in advance was deemed groundbreaking as recently as two decades ago, and a five-day forecast is approximately 80 percent accurate today. Most meteorologists anticipate an increase in accuracy by 2030 as a result of artificial intelligence being used in numerical weather prediction models. Below are a few other forecasting trends to monitor in 2023 besides the improvement in accuracy.

Hyper-relevant Forecasting

Similar to how other types of analytics have become more customized or user-specific, weather intelligence is bringing forecast relevance to a certain enterprise or institution. A firm can select which hazards are most relevant to its operations, such as wind gusts, lightning, severe rainfall, and ice accumulation, and then be notified when those risk thresholds are reached. While the use of hyper-relevant forecasting is increasing among utilities, municipalities, and other infrastructure decision-makers, it is also growing in different industries. By merging meteorological data with purchase habits and consumer demand data, a grocery store chain discovered that a slight temperature change might result in a substantial shift in what consumers buy. The store increased sales by simulating this effect and adjusting inventory management accordingly. Even sports teams use hyper-relevant forecasts for daily stadium operations, food and beverage choices, and strategic gameplay.

Technologically-trained Meteorologists

In today's business world, reporting, forecasting, and analyzing weather data in a manner that can be processed and integrated by numerous stakeholders requires more than meteorological expertise. The weather sector uses a wide range of technical jobs, such as software engineers, data scientists, and app developers, to collect, organize, and provide extensive, sophisticated weather data that is relevant and useful for making crucial decisions. Now, meteorologists see the advantages of possessing data and computer science expertise. In reality, through supplementary curriculum, many colleges help meteorology students acquire useful data science abilities. The University of Washington now offers an option in data science that equips atmospheric science students with computer programming, data management, visualization, and machine learning. Other universities will follow suit. Although the U.S. market is becoming saturated with operational forecasters, meteorologists with sophisticated computer and data science skills will have more chances as technology use grows.