Predicting Climate Variability and Extreme Events

What is seasonal climate prediction?

Climate refers to the average daily and seasonal weather conditions (such as air temperature, humidity, wind, and precipitation). Seasonal climate prediction is the process of estimating the most probable condition of the average surface temperature and precipitation for the future. Climate prediction is typically expressed as the departure from a long-term average, or so-called normal climate. It is expressed in terms of the probability that subsequent seasonally averaged U.S. temperature and precipitation will be below, above, or near this normal climate state. Climate prediction is different from weather prediction in that it forecasts the most probable averaged state of the environment, rather than the daily sequence of environmental changes.

How are seasonal climate predictions made?

A prediction process, whether it is for weather or climate, begins with observing and accurately measuring the most recent and current environmental conditions. For the case of seasonal climate predictions, the most important considerations are the surface boundary conditions (the state of the Earth's surface including such things as soil moisture, snow and ice cover), and the sea surface temperatures over the world's oceans. The reason these are important is because they influence the atmosphere above the surface and typically have long lifetimes that have a cumulative influence on seasonally averaged climate.

The process of making seasonal climate predictions can then be viewed as a two-step process, first involving a prediction of the surface boundary conditions and then predicting how the atmosphere reacts to such conditions. The tools of the forecaster can therefore be based on statistics from historical climate data which have been analyzed to show the relationships between the Earth's surface conditions and climate. There exists roughly a century of reliable historical observations and data to develop such empirical tools. Another tool can be the numerical computer models that represent the physical relationship between the atmospheric variations and variations in surface boundary conditions.

The most common and powerful predictor of seasonal climate is the state of tropical Pacific Ocean associated with the El Niño, a slow periodic warming (or cooling) of the sea surface temperatures there.

Why do we make seasonal climate predictions and who uses them?

Being able to predict seasonal climate can help minimize the possibility of "climate surprises" in order to reduce impacts to society and ecosystems. With these predictions, decision-makers can be provided with reliable scientific information about possible extreme climate events. Many sectors of society use these predictions, including agriculture, fishing, forestry, energy, insurance, public health, water resources, recreation, transportation, health, and construction.

For example, with an increased risk of drought, we know that some possible impacts include water shortages, early onset of the wildfire season, and lower or no crop yields. This in turn could lead to increased disaster assistance payments, higher food prices, and disrupted transportation on internal waterways. With advance knowledge of drought, water resource managers can adjust the timing of water releases from reservoirs, and farmers can alter the type of crops they plant.

Accurate and timely climate information and predictions can help many sectors of society circumvent the impacts posed by climate variations. This reduces the risk of economic setbacks and ecological damage.

This global map shows a strong El Nino in the tropical Pacific

Scientists study El Niño in the tropical Pacific Ocean because it is the most common and powerful predictor of seasonal climate change.

People view a passenger van mired in the mud following a flood.

NOAA research aims to reduce "climate surprises" from extreme climate events including conditions that might cause severe flooding.

NOAA Research programs that study Predicting Climate Variability and Extreme Events

Climate Program Office (CPO)
Earth System Research Laboratory (ESRL)
Atlantic Oceanographic and Meteorological Laboratory (AOML)
Geophysical Fluid Dynamics Laboratory (GFDL)

Additional Related Information:

RESOURCES:

PROGRAMS:

NEXT -- El Niño and La Niña