---

Background:

Extreme events often depend strongly on local physical conditions and small-scale processes, such as convection and interaction with steep topography, which are not well resolved in coarse resolution climate models. Therefore, a high-resolution model is expected to provide a better representation of these processes and consequently extreme events.

Here, we briefly consider three extreme phenomena that are relevant for extreme weather risk assesment and management to illustrate the improvements associated with the finer resolution in CESM-HR:

• Tropical Cyclones:

  Tropical cyclones (TCs) are rapidly rotating, low-pressure systems with features like thunder and lightning that develop in the tropics or subtropics. They can generate multiple devastating hazards including storm surge, flooding, winds of 100 mph or more, and tornadoes. TCs are the most costly weather and climate disasters in the U.S. by far. The current workhorse climate models cannot directly simulate intense TCs due to their relatively low resolution. By contrast, CESM-HR can explicitly simulate Category-4 and Category-5 TCs. CESM-HR simulations are able to reproduce many features of TC climatology, including spatial distribution and intensity distribution, with good fidelity in comparison with observations as illustarted below.

  

  Figure: Observed (top) and simulated TC tracks from CESM-HR (middle) and CESM-LR (lower) during 1950 to 2018. Different colors indicate different storm intensity categories. Vertical dashed lines separate different TC basins (from Chang et al. 2020).

• Atmospheric Rivers:

  Atmospheric rivers (ARs) are defined as relatively long, narrow regions in the atmosphere that transport most of the water vapor outside of the tropics. Most ARs provide beneficial rain or snow that is crucial to the water supply in the western United States. Howevwe, the ARs that carry the largest amounts of water vapor and produce the strongest winds can create extreme rainfall and floods when they make landfall, disrupting travel, inducing mudslides, and causing catastrophic damage to life and property. A well-known example is the "Pineapple Express", a strong atmospheric river that is capable of delivering moisture from the tropics near Hawaii to the U.S. West Coast. The figure below (left panel) shows such an AR simulated in CESM-HR. The panels on the right show the mean integrated vapor transport (IVT) value carried by all the detected ARs over the globe in observations, CESM-HR, and CESM-LR, respectively. Also shown is the averaged precipitation (mm/day) concurrent with ARs. From this figure, it is evident that ARs are much more realistically simulated in CESM-HR than CESM-LR.

  

  Figure: Sample AR as simulated by CESM-HR (left, courtesy of Christine Shields). Total precipitable water (kg/m2) is plotted from the atmosphere component. Feedbacks from the ocean component are reflected onto the precipitable water field via individual oceanic eddies beneath the AR. On the right, Mean IVT (kg/m/s) associated with ARs and averaged precipitation (mm/day) concurrent with ARs in observations (upper), CESM-HR (middle), and CESM-LR (lower). ERA-5 is used as observation for IVT and rainfall observation comes from the 0.25° PERSIANN-CDR (precipitation estimation from remotely sensed information using artificial neural networks-NOAA climate data record) from 1983 to 2005. Zoom-in of AR-related precipitation over the U.S. West Coast are shown in the last column on the right side. Contours indicate orography in these panels.

• Extreme Winter Precipitation over the Continental US:

  Extreme precipitation events have significant impacts on society with ramifications for agriculture, severe flooding, and landslides, among many other things. The Continental U.S. (CONUS) experiences huge economic losses due to severe floods caused by extreme precipitation. Extreme precipitation events have become more intense and more frequent in recent decades, and the observed trends of greater frequency and intensity of extreme storm events are projected to continue or accelerate as the climate warms. Understanding and forecasting future changes in the frequency, intensity, and duration of extreme precipitation events are important for formulating adaptation and mitigation strategies that minimize damages to natural and human systems. Workhorse, coarse resolution climate models lack the resolution to resolve such extreme precipitation events and generally underestimate the rate of occurrence of the most extreme rates of precipitation. The figure bellow shows that simulated extreme winter precipitation in CESM are significantly improved when the horizontal resolution is enhanced. A benefit of the finer resolution is that topography can be expressed in greater detail, improving the spatial correlation between modeled and observed precipitation, especially in the mountainous Western US.

  

  Figure: Winter time extreme daily precipitation over the CONUS (Courtesy of Dan Fu). The maps show the simulated daily mean extreme precipitation during the DJFMAM for the NOAA CPC observavation, CESM-HR, the 4-km CONUS Weather Research and Forecasting (WRF) configuration, and CESM-LR (from left to right and top to bottom respectively). The bottom two panel figures on the right show the daily mean precipitation probability density function (PDF) calculated over the SouthWest and SouthEast U.S. regions. In each panel, the solid black lines is NOAA observation, the dashed black line is PRISM 4km observation, the magenta line is the 4-km CONUS WRF, and red and blue lines are for CESM-HR and CESM-LR, respectively. The pread (shading) indicates the standard deviation across ensemble members.

---

CESM-HR outputs:

CESM-HR global 6-hourly output of the key variables used to identify and track extreme weather events are available via the Globus Guest Collection CESM-HR Extreme Weather Risk dataset for unauthenticated, fast, secure, and reliable data transfer. Data have been regridded to a regular lat-lon grid of 0.25° for convenience.

---

Event Set of risk-relevant weather phenomena:

A catalog of identified and tracked events of relevance to risks, together with contextual environmental information such as global mean surface temperature and climate variability indices will be available soon.

---