Search for: All records

The newly developed paleo‐climate calibrated Community Earth System Model, version 2 (pCESM2) simulates a more realistic global temperature response to external forcing compared to the standard CESM2. Here we show that the code modifications in pCESM2 result in increased atmospheric convection and a northward shift of the Atlantic and eastern Pacific Intertropical Convergence Zones. These changes are exacerbated under Last Glacial Maximum forcing, resulting in tropical precipitation changes that are inconsistent with both proxy data evidence and simulations with other contemporary models. Similar model‐data disagreements are also present in the standard CESM2. Thus, more work is needed to improve the simulated Last Glacial Maximum hydroclimate response in CESM2. We further suggest that well‐constrained paleo climates should be given a larger emphasis in model development more broadly, as these climates can help identify issues with model parameterizations under altered forcing and thus improve the fidelity of simulations of past, present, and future climates.

 

Paleohydrologic proxy data and climate models show how and why eccentricity and precession influenced early Eocene hydroclimate. 

This dataset contains the atmospheric river catalogues and the associated precipitation and temperature data for the Preindustrial and Last Glacial Maximum CESM2 simulations presented in the GRL manuscript:  Atmospheric river contributions to ice sheet hydro climate at the Last Glacial Maximum. The atmospheric river catalogue files (zipped) are in netcdf format and organized by year. There are 100 years of data for both simulations.  The Preindustrial simulation catalogue begins in model year 41 and ends in model year 140.  The LGM simulation catalogue begins in model year 1 and ends in year 100. Each yearly file has a temporal resolution of 6 hours (1460 time steps each file) and a spatial resolution of 0.9° x 1.25° (the native resolution of the CESM simulation). A variable in the file called "ar_binary_tag" indicates whether an atmospheric river is present at each grid cell and each tilmestep: 1 indicates an atmospheric river is present; 0 indicates an atmospheric river is not present.  The precipitation and temperature files are 100-year annual or 100-year seasonal averages of atmospheric river precipitation/temperature. See the Methods section of the article for more details on the atmospheric river detection algorithm and precipitation/temperature calculations.

Associated article abstract:

Atmospheric rivers (ARs) are an important driver of surface mass balance over today’s Greenland and Antarctic ice sheets. Using paleoclimate simulations with the Community Earth System Model, we find ARs also had a key influence on the extensive ice sheets of the Last Glacial Maximum (LGM). ARs provide up to 53% of total precipitation along the margins of the eastern Laurentide ice sheet and up to 22-27% of precipitation along the margins of the Patagonian, western Cordilleran, and western Fennoscandian ice sheets. Despite overall cold conditions at the LGM, surface temperatures during AR events are often above freezing, resulting in more rain than snow along ice sheet margins and conditions that promote surface melt. The results suggest  ARs may have had an important role in ice sheet growth and melt during previous glacial periods and may have accelerated ice sheet retreat following the LGM.

 

Atmospheric rivers (ARs) are an important driver of surface mass balance over today's Greenland and Antarctic ice sheets. Using paleoclimate simulations with the Community Earth System Model, we find ARs also had a key influence on the extensive ice sheets of the Last Glacial Maximum (LGM). ARs provide up to 53% of total precipitation along the margins of the eastern Laurentide ice sheet and up to 22%–27% of precipitation along the margins of the Patagonian, western Cordilleran, and western Fennoscandian ice sheets. Despite overall cold conditions at the LGM, surface temperatures during AR events are often above freezing, resulting in more rain than snow along ice sheet margins and conditions that promote surface melt. The results suggest ARs may have had an important role in ice sheet growth and melt during previous glacial periods and may have accelerated ice sheet retreat following the LGM.

 

Abstract. Equilibrium climate sensitivity (ECS) has been directly estimated using reconstructions of past climates that are different than today's. A challenge to this approach is that temperature proxies integrate over the timescales of the fast feedback processes (e.g., changes in water vapor, snow, and clouds) that are captured in ECS as well as the slower feedback processes (e.g., changes in ice sheets and ocean circulation) that are not. A way around this issue is to treat the slow feedbacks as climate forcings and independently account for their impact on global temperature. Here we conduct a suite of Last Glacial Maximum (LGM) simulations using the Community Earth System Model version 1.2 (CESM1.2) to quantify the forcingand efficacy of land ice sheets (LISs) and greenhouse gases (GHGs) in order to estimate ECS. Our forcing and efficacy quantification adopts the effective radiative forcing (ERF) and adjustment framework and provides a complete accounting for the radiative, topographic, and dynamical impacts of LIS on surface temperatures. ERF and efficacy of LGM LIS are −3.2 W m−2 and 1.1, respectively. The larger-than-unity efficacy is caused by the temperature changes over land and the Northern Hemisphere subtropical oceans which are relatively larger than those in response to a doubling of atmospheric CO2. The subtropical sea-surface temperature (SST) response is linked to LIS-induced wind changes and feedbacks in ocean–atmosphere coupling and clouds. ERF and efficacy of LGM GHG are −2.8 W m−2 and 0.9, respectively. The lower efficacy is primarily attributed to a smaller cloud feedback at colder temperatures. Our simulations further demonstrate that the direct ECS calculation using the forcing, efficacy, and temperature response in CESM1.2 overestimates the true value in the model by approximately 25 % due to the neglect of slow ocean dynamical feedback. This is supported by the greater cooling (6.8 ∘C) in a fully coupled LGM simulation than that (5.3 ∘C) in a slab ocean model simulation with ocean dynamics disabled. The majority (67 %) of the ocean dynamical feedback is attributed to dynamical changes in the Southern Ocean, where interactions between upper-ocean stratification, heat transport, and sea-ice cover are found to amplify the LGM cooling. Our study demonstrates the value of climate models in the quantification of climate forcings and the ocean dynamical feedback, which is necessary for an accurate direct ECS estimation.