Can any climate modelers comment on whether this higher resolution model is a 
big deal for simulating SRM/MCB schemes or not really? 

I’m impressed that it takes a year of computer time to run a 50 year 
simulation. Doesn’t this lag make it a bit less useful?

The fulltext is here: 
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019MS001870

Here is the press summary:

https://www.sciencedaily.com/releases/2020/03/200303113321.htm
Earth supports a breathtaking range of geographies, ecosystems and 
environments, each of which harbors an equally impressive array of weather 
patterns and events. Climate is an aggregate of all these events averaged over 
a specific span of time for a particular region. Looking at the big picture, 
Earth's climate just ended the decade on a high note -- although not the type 
one might celebrate.

In January, several leading U.S. and European science agencies reported 2019 as 
the second-hottest year on record, closing out the hottest decade. July went 
down as the hottest month ever recorded.

Using new high-resolution models developed through the U.S. Department of 
Energy's (DOE) Office of Science, researchers are trying to predict these kinds 
of trends for the near future and into the next century; hoping to provide the 
scientific basis to help mitigate the effects of extreme climate on energy, 
infrastructure and agriculture, among other essential services required to keep 
civilization moving forward.

Seven DOE national laboratories, including Argonne National Laboratory, are 
among a larger collaboration working to advance a high-resolution version of 
the Energy Exascale Earth System Model (E3SM). The simulations they developed 
can capture the most detailed dynamics of climate-generating behavior, from the 
transport of heat through ocean eddies -- advection -- to the formation of 
storms in the atmosphere.

"E3SM is an Earth system model designed to simulate how the combinations of 
temperature, winds, precipitation patterns, ocean currents and land surface 
type can influence regional climate and built infrastructure on local, regional 
and global scales," explains Robert Jacob, Argonne's E3SM lead and climate 
scientist in its Environmental Science division. "More importantly, being able 
to predict how changes in climate and water cycling respond to increasing 
carbon dioxide (CO2) is extremely important in planning for our future."

"Climate change can also have big impacts on our need and ability to produce 
energy, manage water supplies and anticipate impacts on agriculture" he adds, 
"so DOE wants a prediction model that can describe  climate changes with enough 
detail to help decision-makers."

Facilities along our coasts are vulnerable to sea level rise caused, in part, 
by rapid glacier melts, and many energy outages are the result of extreme 
weather and the precarious conditions it can create. For example, 2019's 
historically heavy rainfalls caused damaging floods in the central and southern 
states, and hot, dry conditions in Alaska and California resulted in massive 
wild fires.

And then there is Australia.

To understand how all of Earth's components work in tandem to create these wild 
and varied conditions, E3SM divides the world into thousands of interdependent 
grid cells -- 86,400 for the atmosphere to be exact. These account for most 
major terrestrial features from "the bottom of the ocean to nearly the top of 
the atmosphere," collaboration members wrote in a recent article published in 
the Journal of Advances in Modeling Earth Systems.

"The globe is modeled as a group of cells with 25 kilometers between grid 
centers horizontally or a quarter of a degree of latitude resolution," says 
Azamat Mametjanov, an application performance engineer in Argonne's Mathematics 
and Computer Science division. "Historically, spatial resolution has been much 
coarser, at one degree or about 100 kilometers. So we've increased the 
resolution by a factor of four in each direction. We are starting to better 
resolve the phenomena that energy industries worry about most -- extreme 
weather."

Researchers believe that E3SM's higher-resolution capabilities will allow 
researchers to resolve geophysical features like hurricanes and mountain 
snowpack that prove less clear in other models. One of the biggest improvements 
to the E3SM model was sea surface temperature and sea ice in the North Atlantic 
Ocean, specifically, the Labrador Sea, which required an accurate accounting of 
air and water flow.

"This is an important oceanic region in which lower-resolution models tend to 
represent too much sea ice coverage," Jacob explains. "This additional sea ice 
cools the atmosphere above it and degrades our predictions in that area and 
also downstream."

Increasing the resolution also helped resolve the ocean currents more 
accurately, which helped make the Labrador Sea conditions correspond with 
observations from satellites and ships, as well as making better predictions of 
the Gulf Stream.

Another distinguishing characteristic of the model, says Mametjanov, is its 
ability to run over multiple decades. While many models can run at even higher 
resolution, they can run only from five to 10 years at most. Because it uses 
the ultra-fast DOE supercomputers, the 25-km E3SM model ran a course of 50 
years.

Eventually, the team wants to run 100 years at a time, interested mainly in the 
climate around 2100, which is a standard end date used for simulations of 
future climate.

Higher resolution and longer time sequences aside, running such a model is not 
without its difficulties. It is a highly complex process.

For each of the 86,400 cells related to the atmosphere, researchers run dozens 
of algebraic operations that correspond to some meteorological processes, such 
as calculating wind speed, atmospheric pressure, temperature, moisture or the 
amount of localized heating contributed by sunlight and condensation, to name 
just a few.

"And then we have to do it thousands of times a day," says Jacob. "Adding more 
resolution makes the computation slower; it makes it harder to find the 
computer time to run it and check the results. The 50-year simulation that we 
looked at in this paper took about a year in real time to run."

Another dynamic for which researchers must adjust their model is called 
forcing, which refers mainly to the natural and anthropogenic drivers that can 
either stabilize or push the climate into different directions. The main 
forcing on the climate system is the sun, which stays relatively constant, 
notes Jacob. But throughout the 20th century, there have been increases in 
other external factors, such as CO2 and a variety of aerosols, from sea-spray 
to volcanic.

For this first simulation, the team was not so much probing a specific stretch 
of time as working on the model's stability, so they chose a forcing that 
represents conditions during the 1950s. The date was a compromise between 
preindustrial conditions used in low-resolution simulations and the onset of 
the more dramatic anthropogenic greenhouse gas emissions and warming that would 
come to a head in this century.

Eventually, the model will integrate current forcing values to help scientists 
further understand how the global climate system will change as those values 
increase, says Jacob.

"While we have some understanding, we really need more information -- as do the 
public and energy producers -- so we can see what's going to happen at regional 
scales," he adds. "And to answer that, you need models that have more 
resolution."

One of the overall goals of the project has been to improve performance of the 
E3SM on DOE supercomputers like the Argonne Leadership Computing Facility's 
Theta, which proved the primary workhorse for the project. But as computer 
architectures change with an eye toward exascale computing, next steps for the 
project include porting the models to GPUs.

"As the resolution increases using exascale machines, it will become possible 
to use E3SM to resolve droughts and hurricane trends, which develop over 
multiple years," says Mametjanov.

"Weather models can resolve some of these, but at most for about 10 days. So 
there is still a gap between weather models and climate models and, using E3SM, 
we are trying to close that gap."
Here is the abstract. 


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