Researchers hope ‘to ease comparisons between climate and weather models with observations from weather instruments’, broadly speaking. In terms of modelling this is a known area of difficulty.
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The Earth Model Column Collaboratory is an open-source research platform that pairs complex data with weather observations to create highly accurate climate models and forecast predictions.
Clouds come in all shapes and sizes, says Phys.org.
While we might imagine puppies or whales or breaking waves, climatologists look at them as massive bundles of water in various forms that contribute to the daily weather, and ultimately, climate.
The numbers, shapes and sizes of the liquid drops and ice crystals contained in a cloud, for example, will determine how it will scatter light or emit and absorb heat.
Despite the enormity of clouds, many of these dynamics happen at a small scale. So, to better understand how all those imaginary creatures produce the effects that they do, researchers rely on computer-generated climate models.
These models can bring together information from different weather instruments, physics calculations and other observations to increase our knowledge of how the atmosphere works.
But due to limits in computing power, climate models must simplify the way clouds are represented. This introduces uncertainty in both projections of cloud behavior and climate change.
Typically, in order to improve cloud representations, model results are compared with observations. However, the climate model and observation communities have historically worked separately, sometimes making the process hard to navigate.
To bridge the gap between these two communities, climate scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, Pennsylvania State University and the NASA Goddard Institute for Space Studies developed an easier way to compare cloud models with observations from weather instruments.
The result is a modeling platform and weather instrument simulator called the Earth Model Column Collaboratory (EMC²).
Results from current climate models don’t directly compare to those from radars, satellites and other sensors whose signals can’t directly detect key cloud parameters like liquid water content and number of drops.
Instead, they detect microwave and visible light reflected by clouds and precipitation. As an instrument simulator, EMC² can convert the more detailed model-simulated cloud parameters to these weather instrument signals.
Another complication in climate modeling is the size of the geographic areas researchers want to study.
Full article here.
via Tallbloke’s Talkshop
October 13, 2022, by oldbrew