"Numerical climate models are used for a variety of purposes from study of the dynamics of the climate system to projections of future climate."
The process of using computer models to simulate the Earth's climate and predict future changes.
Earth's Climate System: Understanding the fundamental components of earth's climate system (atmosphere, hydrosphere, biosphere, and lithosphere) and the interactions between them is foundational for climate modeling.
Climate Changes: Studying observed changes in climate patterns and understanding the drivers of these changes is important for developing models that can accurately predict future climate trends.
Atmospheric Dynamics: Understanding how atmospheric variables, such as temperature, pressure, wind, and humidity, interact with each other and with the earth's surface is essential for climate modeling.
Radiative Transfer: Understanding the transfer of energy from the sun and from the earth's surface through the atmosphere is important for predicting future climate scenarios.
Climate Forcing: Understanding the natural and anthropogenic factors that drive climate change, such as greenhouse gas emissions, solar radiation, and volcanic activity, is important for climate modeling.
Atmospheric Physics: Understanding the physical processes that shape the behavior of the atmosphere, such as convection, advection, and turbulence, is essential for climate modeling.
Ocean-Atmosphere Interactions: Understanding the interactions between the ocean and atmosphere, such as ocean currents, ocean heat transport, and ocean mixing, is important for developing accurate climate models.
Land Surface-Ecosystem Interactions: Understanding how surface processes, such as vegetation growth and land use change, affect atmospheric processes is important for accurate climate modeling.
Climate Modeling Techniques: Understanding the various numerical methods used to simulate climate processes, including numerical weather prediction, coupled ocean-atmosphere models, and climate models, is essential for developing accurate climate models.
Model Evaluation: Understanding how to evaluate climate models for their accuracy and reliability, using techniques such as data assimilation, model comparison, and uncertainty analysis, is important for improving climate model performance.
Global Climate Models (GCMs): These are the most common type of climate models that use complex mathematical equations to simulate the global climate system, including the atmosphere, oceans, land surface, and sea ice. GCMs generate output at a spatial resolution of typically 100-200 km.
Regional Climate Models (RCMs): These models simulate climate phenomena at a regional scale, typically at a resolution of 5-50km. They start with output from global models and make specific predictions about changes in weather patterns or average climate in a particular region.
Earth System Models (ESMs): These models simulate a range of earth systems for projecting future climate change. It integrates modeling of the climate system with the carbon cycle, land use and land cover change, biogeochemical cycling, and nutrient cycling.
Statistical models: These models use statistical algorithms to identify and quantify relationships between climate variables. These models use the relationships identified to make future climate projections.
"Numerical climate models simulate the interactions of the important drivers of climate, including atmosphere, oceans, land surface and ice."
"Climate models may also be qualitative (i.e. not numerical) models and also narratives, largely descriptive, of possible futures."
"Quantitative climate models take account of incoming energy from the sun as short wave electromagnetic radiation, chiefly visible and short-wave (near) infrared, as well as outgoing long wave (far) infrared electromagnetic."
"An imbalance results in a change in temperature."
"A simple radiant heat transfer model treats the Earth as a single point and averages outgoing energy."
"This can be expanded vertically (radiative-convective models) and/or horizontally."
"Coupled atmosphere-ocean-sea ice global climate models solve the full equations for mass and energy transfer and radiant exchange."
"In addition, other types of modeling can be interlinked, such as land use, in Earth System Models."
"This allows researchers to predict the interaction between climate and ecosystems."
"Quantitative climate models use quantitative methods to simulate climate interactions while qualitative models are largely descriptive narratives of possible futures."
"Numerical climate models simulate the interactions of the important drivers of climate, including atmosphere, oceans, land surface, and ice."
"Quantitative climate models take account of incoming energy from the sun as short wave electromagnetic radiation, chiefly visible and short-wave (near) infrared, as well as outgoing long wave (far) infrared electromagnetic."
"Numerical climate models are used for a variety of purposes from study of the dynamics of the climate system to projections of future climate."
"An imbalance results in a change in temperature."
"A simple radiant heat transfer model treats the Earth as a single point and averages outgoing energy."
"This can be expanded vertically (radiative-convective models) and/or horizontally."
"Coupled atmosphere-ocean-sea ice global climate models solve the full equations for mass and energy transfer and radiant exchange."
"In addition, other types of modeling can be interlinked, such as land use, in Earth System Models."
"This allows researchers to predict the interaction between climate and ecosystems."