We enhance the Community Land Model (CLM) snow albedo modeling by implementing several new features with more realistic and physical representations of snow-aerosol-radiation interactions. Specifically, we incorporate the following model enhancements: (1) updating ice and aerosol optical properties with more realistic and accurate datasets, (2) adding multiple dust types, (3) adding multiple surface downward solar spectra to account for different atmospheric conditions, (4) incorporating a more accurate adding-doubling radiative transfer solver, (5) adding nonspherical snow grain representation, (6) adding black carbon-snow and dust-snow internal mixing representations, and (7) adding a hyperspectral (480-band versus the default 5-band) modeling capability. These model features/enhancements are included as new CLM physics/namelist options, which allows for quantification of model sensitivity to snow albedo processes and for multi-physics model ensemble analyses for uncertainty assessment. The model updates will be included in the next CLM version release. Sensitivity analyses reveal stronger impacts of using the new adding-doubling solver, nonspherical snow grains, and aerosol-snow internal mixing than the other new features/enhancements. These enhanced snow albedo representations improve the CLM simulated global snowpack evolution and land surface conditions, with reduced biases in simulated snow surface albedo, snow cover, snow water equivalent, snow depth, and surface temperature, particularly over northern mid-latitude mountainous regions and polar regions.

Radiation-topography interaction plays an important role in the surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of radiation-topography interaction over the TP. Land-atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for radiation-topography interaction overall improves E3SM’s performance in simulating surface climate. The winter cold bias in air temperature decreases from -4.48 K to -3.70 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP’s radiation-topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts.

Many regions across the globe broke their surface temperature records in recent years, further sparking concerns about the impending arrival of “tipping points” later in the 21st century. This study analyzes observed global surface temperature trends in three target latitudinal regions: the Arctic Circle, the Tropics, and the Antarctic Circle. We show that global warming is accelerating unevenly across the planet, with the Arctic warming at approximately three times the average rate of our world. We further analyzed the reliability of latitude-dependent surface temperature simulations from a suite of Coupled Model Intercomparison Project Phase 6 models and their multi-model mean. We found that GISS-E2-1-G and FGOALS-g3 were the best-performing models based on their statistical abilities to reproduce observational, latitude-dependent data. Surface temperatures were projected from ensemble simulations of the Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5). We estimate when the climate will warm by 1.5, 2.0, and 2.5 ℃ relative to the preindustrial period, globally and regionally. GISS-E2-1-G projects that global surface temperature anomalies would reach 1.5, 2.0, and 2.5 ℃ in 2024 (±1.34), 2039 (±2.83), and 2057 (±5.03) respectively, while FGOALS-g3 predicts these “tipping points” would arrive in 2024 (±2.50), 2054 (±7.90), and 2087 (±10.55) respectively. Our results reaffirm a dramatic, upward trend in projected climate warming acceleration, with upward concavity in 21st century projections of the Arctic, which could lead to catastrophic consequences across the Earth. Further studies are necessary to determine the most efficient solutions to reduce global warming acceleration and maintain a low SSP, both globally and regionally.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.

The sub-seasonal features of the annual trends of runoff and other associated hydroclimatic variables in the upper Colorado River basin (UCRB) are examined using multiple datasets from in-situ observations, reanalysis, and modeling for early spring (February, March, and April), given that about 58% of annual mean runoff decline from 1980 to 2018 stem from its decreases in the three months. Our analysis suggests that the strong annual trends of hydroclimatic variables in March are more statistically significant than other two months. While recent observational studies attribute the declining runoff to regional warming and precipitation decrease, we suggested, for the first time, that a larger decreasing trend of the runoff in March is caused by the declining cloud optical depth which induces further decrease in precipitation and additional increase in temperature on top of climatic warming. The recent cloud suppression likely results from stronger subsidence and larger moisture flux divergence over southwestern United States because of abnormal circulation patterns in varying climate, in turn leading to drier atmosphere which is unfavorable for cloud formation/development over the UCRB region. The cloud influence on the runoff in March in the UCRB observed in this study implies the importance of understanding sub-seasonal variations of hydroclimate in the changing climate, as well as a need of future studies on the response of circulation patterns to climate change at sub-seasonal level and its implication on local hydroclimate.