Climate modeling
Other sciences such as biology and chemistry can perform repeated sets of experiments to test their hypotheses. Unless we are able to find, colonize and perform experiments on other planetary bodies with the same characteristics as Earth, Earth science will remain very different than these other fields. In absence of the ability to run experiments, Earth Science relies on numerical modeling experiments.
The models project possible climates based on scenarios that cover a range of assumptions about global population, greenhouse gas emissions, technologies, fuel sources, etc. The model results provide a range of possible impacts based on these assumptions.
The models project possible climates based on scenarios that cover a range of assumptions about global population, greenhouse gas emissions, technologies, fuel sources, etc. The model results provide a range of possible impacts based on these assumptions.
Global Indicators
Numerical models of the Earth are composed of set of equations intended to capture a variety of processes that occur on the Earth. These processes include things as simple as representing gravity, to more complex processes involving vegetation, the water cycle and the atmosphere. Climate integrates the atmosphere, ocean, biosphere, cryosphere and hydrosphere and hence climate models attempt to capture models of each of these spheres and well as their interactions.
Climate models simulate Earth's climate system with a 3-dimensional grid that extends through the land, ocean, and atmosphere. The grids have 10 to 60 different levels in the atmosphere with grid spacings of 100 by 150 km. How many grid cells would cover Idaho? The models perform trillions of calculations that describe changes in many climate factors in the grid.
Climate models simulate Earth's climate system with a 3-dimensional grid that extends through the land, ocean, and atmosphere. The grids have 10 to 60 different levels in the atmosphere with grid spacings of 100 by 150 km. How many grid cells would cover Idaho? The models perform trillions of calculations that describe changes in many climate factors in the grid.
Climate models have been developed over the past 30 years and vary in their complexity. We use these models to develop seasonal climate outlooks. For example, in predicting the onset of El Nino and what it means for winter climate in the Pacific Northwest.
Models are meant to guide provide guidance and may not always be "correct". We use pieces of these climate models today. The atmospheric component of climate models are used in numerical weather prediction in developing our weather forecasts. These models are not always spot on, but they same innumerable lives and money and have proven value in helping society cope with weather.
Relating global climate change projections to regional, or even local, effects is critical for making policy and investment choices that can reduce the potential for future adverse climate impacts.
Climate projections versus weather predictions
A common critique of climate predictions is, "If weather model forecasts aren't reliable more than a week out, how can models predict climate decades in the future?" Weather and climate models are based on similar physics, although climate models incorporate the influence of the ocean, biosphere, and cryosphere. Weather forecasts look at the day-to-day changes on a local level and try to predict exactly what will happen at a given place on a given date. Subtle chaotic atmospheric variations make short-term weather forecasts difficult beyond 8-10 days. Climate predictions are focused on longer term processes and global or regional scales. Climate models deal with the longer-term influences of the sun, oceans, land, and ice on the atmosphere. They do not try to predict the weather on a given day, but rather project the statistics of climate for decades or centuries.
Let's see a climate model in action. We'll look at a simulation of one year of data that shows water vapor across the globe. See if you recognize the features of the circulation.
Models are meant to guide provide guidance and may not always be "correct". We use pieces of these climate models today. The atmospheric component of climate models are used in numerical weather prediction in developing our weather forecasts. These models are not always spot on, but they same innumerable lives and money and have proven value in helping society cope with weather.
Relating global climate change projections to regional, or even local, effects is critical for making policy and investment choices that can reduce the potential for future adverse climate impacts.
Climate projections versus weather predictions
A common critique of climate predictions is, "If weather model forecasts aren't reliable more than a week out, how can models predict climate decades in the future?" Weather and climate models are based on similar physics, although climate models incorporate the influence of the ocean, biosphere, and cryosphere. Weather forecasts look at the day-to-day changes on a local level and try to predict exactly what will happen at a given place on a given date. Subtle chaotic atmospheric variations make short-term weather forecasts difficult beyond 8-10 days. Climate predictions are focused on longer term processes and global or regional scales. Climate models deal with the longer-term influences of the sun, oceans, land, and ice on the atmosphere. They do not try to predict the weather on a given day, but rather project the statistics of climate for decades or centuries.
Let's see a climate model in action. We'll look at a simulation of one year of data that shows water vapor across the globe. See if you recognize the features of the circulation.
Next lets see if we can use these models to help answer some of our questions. We have observed changes in climate over the past century and have outlined possible factors that might be behind them. We are going to use several climate models are run two experiments on them. Experiment #1 will use only natural climate forcings, including solar variability and volcanic eruptions. The second experiment will also include anthropogenic forcing. Remind yourself of the increases in atmospheric carbon dioxide by viewing changes here. We will run these experiments from 1850-2000.
Experiment Results
Experiment #1 (below) shows the observed time series of global temperature (black) and 20 different model runs that considered natural forcings (individual thin blue lines). Experiment #2 (top) shows the results for all forcing.
Experiment #1 fails to replicate the observed changes in global temperature, particularly after 1950. By contrast, Experiment #2 replicates most of the warming. Note that no model captures all of the year-to-year variability. Models all simulate their own natural variability (El Nino), and so this is not expected. However, these experiments show that the warming is unable to explain the warming without including anthropogenic forcing. These experiments help further implicate mankind in climate change to date.
Experiment #1 fails to replicate the observed changes in global temperature, particularly after 1950. By contrast, Experiment #2 replicates most of the warming. Note that no model captures all of the year-to-year variability. Models all simulate their own natural variability (El Nino), and so this is not expected. However, these experiments show that the warming is unable to explain the warming without including anthropogenic forcing. These experiments help further implicate mankind in climate change to date.