Long-Term Weather Patterns
Long-term weather patterns refer to significant atmospheric phenomena that persist over extended periods, influencing climate and weather conditions across different regions. These patterns, which can last from months to years, are crucial for understanding past climate changes and predicting future shifts. Key examples include the El Niño Southern Oscillation (ENSO), which encompasses both El Niño and La Niña phases. El Niño is characterized by warmer ocean waters in the eastern Pacific, leading to diverse weather impacts globally, such as increased precipitation or droughts in different areas. Conversely, La Niña results in cooler ocean temperatures, often causing colder winters in certain regions and increased hurricane activity in the Atlantic.
Other notable patterns include the Arctic Oscillation (AO) and the Madden-Julian Oscillation (MJO). The AO affects winter weather through alternating pressure systems in the Arctic and mid-latitudes, while the MJO influences tropical rainfall patterns, particularly during monsoon seasons. Meteorologists use advanced data-gathering techniques, including satellite observations, to track these patterns and develop predictive models, helping societies prepare for potential weather impacts. Understanding these long-term weather patterns is increasingly important as climate change continues to alter established weather norms.
Long-Term Weather Patterns
Much work in meteorology is dedicated to accurately predicting short-term weather patterns. However, an essential part of meteorology is the pursuit of information on long-term trends and conditions. This field involves the study of consistent weather conditions that develop and continue through months and years. The field also entails understanding certain phenomena that contribute to these extended weather periods. Research on long-term weather patterns can help scientists understand past climate changes and predict future shifts, enabling society to better prepare for such weather changes.
A carefully watched long-term weather pattern is the phenomenon known as El Niño, also known as El Niño Southern Oscillation (ENSO). El Niño is a cyclical event in which warm ocean water (which is heated at the equator) moves eastward from the western Pacific Ocean because of stagnation in the trade winds (which blow from east to west along the equator).
Normally, the trade winds send the solar-heated water westward, where the resulting humidity creates weather patterns that travel worldwide. With El Niño, the warm water moves eastward, creating new weather systems and (because of El Niño’s distinctive sea-level pressure signature) shifting how the global atmosphere circulates.
El Niño has different effects on different regions of the world. For example, evidence suggests that El Niño contributes to the generation of powerful, tornado-producing storms in the prairie regions of the United States and Canada. For other regions, such as the Atlantic seaboard, El Niño can mean more precipitation in the form of snowstorms, nor’easters (large rotating Atlantic coastal storms capable of high winds and heavy precipitation), and other systems. In South America, ENSO can cause storms that produce severe flooding.
In some regions, El Niño can lead to less precipitation. For example, El Niño often means less snow than usual in the Rockies and southwestern Canada. Meanwhile, in Australia, El Niño patterns frequently cause droughts. ENSO is even known to reduce the number and severity of hurricanes, which form in the typically warm waters off western Africa.
El Niño can last between two and seven years. While it is a cyclical event, its appearance is typically erratic. For example, the longest lasting El Niño event recorded during the modern era lasted from 1990 to 1995. However, since 1995, the El Niño cycle has been shorter, lasting one or two years on average. For example, from 2018 to 2019, there was a short and weak El Niño event. The El Niño event that occurred in 2023 and 2024, however, lasted from July 4, 2023 to early March 2024.
La Niña
When ENSO periods close, the trade winds intensify because of the difference in surface-level air pressure. The winds blow the warmer water westward and from the west coasts of North and South America.
As the warm water is carried west, cooler water from beneath the eastern Pacific Ocean surface is drawn to the surface. As is the case during El Niño, the cooling water again causes a change in atmospheric circulation, creating changes in the jet streams (a global band of strong air currents several miles above the Earth’s surface). As a result, weather patterns change. This pattern is known as La Niña.
La Niña is considered the latter half of the ENSO cycle. Like El Niño, La Niña’s effect on the weather varies by region. For example, warmer water in the western Pacific leads to wetter weather conditions in Indonesia and Australia. In the United States, colder weather frequently exists in the northwest region, while the southern and mid-Atlantic see warmer and drier conditions.
La Niña also results in changes in severe weather patterns. For example, the generation of major storms that produce hail and tornadoes is reduced by the cooler, drier air manifest during La Niña. However, La Niña disrupts the wind shear (the difference in wind speed and direction in two close areas of the atmosphere), which can hinder the development of tropical storms in the Atlantic. This disruption results in an increase in the number and severity of Atlantic hurricanes.
Arctic Oscillation
ENSO is not the only atmospheric cycle. Another long-term weather pattern, the Arctic Oscillation (AO) system, involves two atmospheric pressure areas. These two patterns are located at the polar latitude (above the Arctic Circle) and the middle latitude (between southern Florida and the Arctic Circle).
There are two phases in which the AO is manifest. These phases have alternated frequently during the last century, with each phase lasting between ten and forty years. During the negative phase, higher-than-normal pressure is in place in the Arctic regions, while lower pressure exists at the middle latitudes (such as most of North America and Europe). These conditions cause cold air to move into the middle latitudes, which leads to colder-than-average winters in these regions. During the positive phase, however, the patterns are reversed: Ocean storms and wetter weather are drawn into the northernmost regions of North America and Europe, while the middle latitudes remain drier and warmer.
Several factors contribute to the change in phases within the AO cycle, including the pressures associated with rising and lowering sea levels, water temperatures, and even greenhouse gases. AO is closely related to two other regional oscillation patterns: the North Atlantic Oscillation and the northern annual mode, which affect winter weather patterns in the North American and Northern European and Asian regions, respectively.
Madden-Julian Oscillation
Still another type of long-term weather pattern is the Madden-Julian Oscillation (MJO). The MJO is intraseasonal (it can develop within thirty, sixty, or ninety days of a given season) and occurs across the planet’s tropical regions (particularly in the Indian and Pacific Oceans). It is also global, traveling in a wave in the atmosphere.
Depending on the phase of the MJO, this long-term weather pattern is responsible for generating and suppressing heavy tropical rainfall (including the high precipitation accompanying monsoons). The MJO’s phase of high-volume precipitation first begins in the Indian Ocean and then proceeds east toward the western and eastern Pacific. As it approaches the cooler waters of the eastern Pacific, the MJO tends to become less laden with precipitation as the heat from warmer water dwindles. The MJO does show some limited life in the tropical Atlantic but becomes noticeable again as it reapproaches the Indian Ocean.
The MJO is a more vexing long-term weather pattern to study and predict because of its relatively slow movement and development along the tropical path. The key to its ability to develop and strengthen storm systems is the warm waters over which it passes. Therefore, scientists are attempting to pinpoint the locations of these pockets of warm water through the use of satellite sensors, developing models that may one day enable them to better understand and predict MJO movements.
Models for Forecasting Long-Term Patterns
Meteorologists and climatologists see great value in the analysis and prediction of long-term weather patterns. A season-by-season weather forecast can help scientists prepare for weather patterns.
For example, tracking La Niña during winter can help researchers forecast enhanced or subdued storm systems in a given geographic area. For this reason, scientists are working to better track and predict the more erratic AO and MJO. Furthermore, any evidence of above- or below-average precipitation is helpful for the residents of these regions to prepare for the effects of these long-term weather patterns.
Scientists utilize several approaches to track and predict long-term weather patterns. First, they gather data on surface-level conditions (such as water temperatures and wind speeds) and weather patterns collected from satellite, airborne, remote, and ground-based systems. Using these data, they generate mathematical equations that represent each of the physical processes at work. For example, scientists have developed a series of mathematical equations designed to assign values to circulation anomalies within the MJO; such equations help researchers better understand how such elements influence the MJO’s atmospheric dynamics.
Once the data have been compiled and collated, they form computer models that predict future conditions created by a given long-term weather pattern. One example comes from Japan, whose Ministry of Science utilized the Earth simulator supercomputer—once the fastest computer in the world—to compile global weather data, including long-term weather patterns, ocean currents, and other factors, into a massive model. Since 2022, scientists have been using the Earth simulator, in its fourth generation in 2024, to attempt to predict droughts, severe storms, and other weather and climate conditions as far as thirty years into the future.
Other computer models focus on a particular long-term weather pattern and analyze its individual elements, such as regional cold temperature zones along an ENSO track or the relationship between atmospheric circulation and surface-level conditions. For example, the National Weather Service in the United States operates a climate prediction center, which compiles a wide range of sensor data on surface and water temperature, wind velocity, precipitation, and air currents (and on anomalies in these conditions based on seasonal averages). Based on this information, the center generates seasonal short- and long-term forecasts, tracking weather systems based on the influences of ENSO, AO, MJO, and other patterns. Further, understanding the effects of climate change has become another important factor in understanding long-term weather patterns in the twenty-first century.
Principal Terms
Arctic oscillation: long-term weather pattern in which the different air pressures in the Arctic and middle latitude regions cause varying weather conditions
El Niño: a meteorological condition in which the waters of the tropical, eastern Pacific Ocean are warmed by the atmosphere
La Niña: a meteorological condition in which the waters of the eastern, tropical Pacific Ocean are cooled by a lack of radiation from the atmosphere
Madden-Julian oscillation: intraseasonal tropical wave that travels around the globe, causing monsoons and other high-water storms and also suppresses them
trade winds: winds at the level of the ocean surface that blow from the east to the west in the tropical Pacific
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