Jing Zhang

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1‐Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1‐Arctic) historical simulations (1950–2014) with the uniform low‐resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large‐scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high‐resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

This paper provides an overview of the United States (U.S.) Department of Energy’s (DOE’s) Energy Exascale Earth System Model version 2.1 with an Arctic regionally refined mesh (RRM), hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950-2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational datasets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice dynamics. However, the RRM introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter. The RRM also underestimates winter sea ice area and volume, consistent with its strong winter warm bias. Radiative feedback analysis shows similar climate feedback strengths in both RRM and LR, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10-100 km scales.

Snow, a critical element influencing surface energy/mass balance of the Arctic, can also drift in the air to complicate the surface–atmosphere interaction. This complexity can be further enhanced when the surface includes polynya. These processes, however, have not been well studied and are often unrepresented in climate and weather models. We address this by applying a snow/ice-enhanced version of the Weather Research and Forecasting model to examine the impacts of blowing snow and polynya on the surface–atmosphere interaction during an extreme Arctic wind event in February 2018, when an unprecedented polynya occurred off the north coast of Greenland. The results indicate that blowing snow and the polynya contribute opposite signs to the changes of surface sensible/latent heat fluxes, but both cause enhanced downwelling longwave radiation. Process analysis shows that the thermodynamic moistening/cooling effects due to the blowing snow sublimation are amplified by increased surface winds, reduced temperature inversion, and upward wind anomaly associated with the polynya. Enhanced surface–atmosphere interaction over a polynya due to blowing snow sublimation can potentially sustain the continuing development of the polynya.

The impacts of blowing snow, a very common snow‐air interactive process over Antarctica, are investigated with a snow/ice enhanced Weather Research and Forecasting (WRF‐ice) model for the surface energy budget (SEB) and surface mass balance (SMB) modeling over the Larsen C Ice Shelf (LCIS), Antarctic Peninsula. The net effect of blowing snow on LCIS' SMB is negative, because the positive effect of enhanced precipitation, reduced surface sublimation, and blowing snow transport is more than compensated by the negative effect of blowing snow sublimation, enhanced surface melt, and runoff. In sum, blowing snow contributes to positive anomalies in LCIS' SEB and negative anomalies in SMB.

To better capture the air‐snow‐ice interaction, a snow/ice enhanced Weather Research and Forecasting (WRF‐ice) model has been developed. This study examines the performance of WRF‐ice and its blowing snow component during a strong cyclone event from October 23 to 27, 2017 over the Antarctic Peninsula, which is characterized by a synoptic cyclone crossing the northern part of the Peninsula and an embodied mesoscale cyclone over the Weddell Sea. Evolution of the cyclone is accurately reproduced in the 5‐km resolution WRF‐ice simulation, and the simulated near‐surface conditions agree well with station and satellite observations. Numerical simulations show that the process of blowing snow sublimation can be prominent within the lower atmosphere when the air is dry, and produces moistening and cooling effects. Over relatively warm and humid areas, cloud enhancement by blowing snow can lead to either colder or warmer surfaces because of competing effects of longwave and shortwave cloud radiative forcings. In particular, additional moisture from blowing snow sublimation can slightly intensify precipitation over the mountains. Surface energy budget analysis indicates that absorbed shortwave (S_a), incoming longwave (L_d), and outgoing longwave (L_u) are dominant components of surface energy budget. When increases in L_d, L_u, and sensible heat flux are combined with decreases in S_a and latent heat flux due to blowing snow effects, a negative surface net heat flux (∼0.5 W/m²) occurs during daytime. A positive domain‐total surface mass balance (∼0.43 Gt) is generated during the simulated cyclone event due to increases in precipitation, decreases in runoff, and decreases in sublimation.

Extensive field observations were conducted in the Upper Susitna basin, a 13 289 km² glacierized catchment in central Alaska in 2012–2014. This paper describes the comprehensive data set of meteorological, glacier mass balance, snow cover, and soil measurements, as well as the data collection and processing. Results are compared to similar observations from the 1980s. Environmental lapse rates measured with weather stations between about 1000 and 2000 m a.s.l. were significantly lower over the glaciers than the non-glacierized areas. Glacier-wide mass balances shifted from close to balanced in 1981–1983 to less than −1.5 m w.e. yr⁻¹ in 2012–2014. Winter snow accumulation measured with ablation stakes on the glaciers closely matched observations from helicopter-borne radar. Soil temperature measurements across the basin showed that there was no permafrost in the upper 1 m of the soil column. The data produced by this study are available at: https://doi.org/10.14509/30138 (Bliss et al., 2019) and will be useful for hydrological and glaciological studies including modeling efforts.

As part of a planned hydropower facility, extensive field observations were conducted in the Upper Susitna basin, a 13,289 km² glacierized catchment in central Alaska in 2012–2014. This paper describes a comprehensive data set of meteorological, glacier mass balance, snow cover and soil measurements, as well as the data collection and processing. Results are compared to similar observations from the 1980s. Environmental lapse rates measured with weather stations between about 1000 and 2000 m a.s.l. were significantly lower over the glaciers than the non-glaciated areas. Glacier-wide mass balances shifted from close to balanced in the 1980s to less than −1.5 m w.e. yr⁻¹ in 2012–2014. Winter snow accumulation measured with ablation stakes on the glaciers closely matched observations from helicopter-borne radar. Soil temperature measurements across the basin showed that there was no permafrost in the upper 1 m of the soil column. The data produced by this study is available at https://doi.org/10.14509/30138 and will be useful for hydrological and glaciological studies including modeling efforts