Episode 39: Climate Models

In this episode of the podcast, I have talked about “Climate Models.” Climate models are an important tool for scientists to understand the complexities of Earth’s climate. These computer simulations incorporate both theory and direct observations of the past and present in order to project climate into the future. Because of this synthesizing role, and because their output takes the recognizable shape of maps, these models lay an important foundation for political action on climate change.

Additional Info:
Climate models can be tested through forecasts based on initial conditions. Climate models are closely related to the models that are used routinely for numerical weather prediction, and increasingly for extended range forecasting on seasonal to interannual time scales.
With Earth’s climate as their subject, these models have taken on an enormous challenge. Although climate is often thought of as just an average temperature or is confused with the weather of a single season, climate is generally defined as the average state of weather over a period of years at a given location. This includes the mean values and ranges of variables such as wind, temperature, precipitation, humidity, cloudiness, pressure, visibility and air quality. These variables are strongly connected to the rest of the natural world, meaning that climate also involves other aspects of the atmosphere, oceans, land surface and ice (the cryosphere). Therefore, climate is not a single thing, but instead a sprawling system of many processes that interact with each other in complicated ways. This system is affected by external factors, like radiation from the sun, volcanic eruptions, and changes in Earth’s orbit. The climate system also influences, and is influenced by, other natural processes like evaporation and photosynthesis. Consequently, climate models grow increasingly complex as they more accurately reflect these intricacies. Sophisticated models, like Coupled General Circulation Models, combine many processes to portray the entire climate system. The most important components of these models are the atmosphere (including air temperature, moisture and precipitation levels, and storms); the oceans (measurements such as ocean temperature, salinity levels, and circulation patterns); terrestrial processes(including carbon absorption, forests, and storage of soil moisture); and the cryosphere (both sea ice and glaciers on land). A successful climate model must not only accurately represent all of these individual components, but also show how they interact with each other. The obtained best-fit climate sensitivity estimates differ for various reasons from other estimates that were derived with alternative methods. Such alternative methods include, for example, regression estimates that use a global energy balance equation around the year of atmospheric CO2 doubling or the analysis of slab ocean equilibrium warmings. The resulting differences in climate sensitivity estimates can be partially explained by the non-time constant effective climate sensitivities in many of the AOGCM runs. Furthermore, tuning results of a simple climate model will be affected by the model structure, although simple, and other default parameter settings that affect the simple model transient response.

Twitter: https://twitter.com/realyashnegi
Website: climatology.in
Email: yashnegi@climatology.in
Song: Ikson - New Day (Vlog No Copyright Music)