In this study, a global variable-resolution modeling framework of atmospheric dust and its radiative feedback is established and evaluated. In this model, atmospheric dust is simulated simultaneously with meteorological fields, and dust-radiation interactions are included. Five configurations of global mesh with refinement at different resolutions and over different regions are used to explore the impacts of regional refinement on modeling dust lifecycle at regional and global scales. The model reasonably produces the overall magnitudes and spatial variabilities of global dust metrics such as surface mass concentration, deposition, aerosol optical depth, and radiative forcing compared to observations and previous modeling results. Two global variable-resolution simulations with mesh refinement over major deserts of North Africa (V16 km-NA) and East Asia (V16 km-EA) simulate less dust emissions and smaller dry deposition rates inside the refined regions due to the weakened near-surface wind speed caused by better resolved topographic complexity at higher resolution. The dust mass loadings over North Africa are close to each other between V16 km-NA and the quasi-uniform resolution (similar to 120 km) (U120 km), while over East Asia, V16 km-EA simulates higher dust mass loading. Over the non-refined areas with the same resolution, the difference between global variable-resolution and uniform-resolution experiments also exists, which is partly related to their difference in dynamic time-step and the coefficient for horizontal diffusion. Refinement at convection-permitting resolution around the Tibetan Plateau (TP) simulates less dust due to its more efficient wet scavenging from resolved convective precipitation around the TP against coarse resolution. Mineral dust plays an important role in Earth's climate system. Numerical simulation of dust and its impacts on a regional scale still has large uncertainties, partly due to the relatively coarse horizontal resolution. Limited-area simulation at relatively high resolution can generally better characterize dust and its impacts on a regional scale; however, lateral boundary conditions may introduce some numerical issues and constrain regional feedback, such as dust-cloud and dust-radiation interactions, to large-scale circulation. In this study, a novel modeling framework of atmospheric dust and its climatic feedbacks with the capability of global variable-resolution simulation is established and evaluated. The model produces reasonable global spatial distributions of dust compared to observations and previous studies. The difference between the simulations at global quasi-uniform resolution and global variable resolution with regional refinement over East Asia and North Africa is significant, particularly with refinement at convection-permitting resolution. This model may be used in the future to provide new insights into the impacts of dust on regional and global climate systems. A modeling framework of atmospheric dust with the capability of global variable-resolution simulation is introduced and evaluatedExperiments with regional refinement produce less dust emissions and mass loading and smaller dry deposition due to weaker surface windRefinement at convection-permitting resolution simulates stronger wet scavenging and less dust mass compared to coarse resolution

Aerosol processes and, in particular, aerosol-cloud interactions cut across the traditional physical-Earth system boundary of coupled Earth system models and remain one of the key uncertainties in estimating anthropogenic radiative forcing of climate. Here we calculate the historical aerosol effective radiative forcing (ERF) in the HadGEM3-GA7 climate model in order to assess the suitability of this model for inclusion in the UK Earth system model, UKESM1. The aerosol ERF, calculated for the year 2000 relative to 1850, is large and negative in the standard GA7 model leading to an unrealistic negative total anthropogenic forcing over the twentieth century. We show how underlying assumptions and missing processes in both the physical model and aerosol parameterizations lead to this large aerosol ERF. A number of model improvements are investigated to assess their impact on the aerosol ERF. These include an improved representation of cloud droplet spectral dispersion, updates to the aerosol activation scheme, and black carbon optical properties. One of the largest contributors to the aerosol forcing uncertainty is insufficient knowledge of the preindustrial aerosol climate. We evaluate the contribution of uncertainties in the natural marine emissions of dimethyl sulfide and organic aerosol to the ERF. The combination of model improvements derived from these studies weakens the aerosol ERF by up to 50% of the original value and leads to a total anthropogenic historical forcing more in line with assessed values.

Agro-ecosystem models, such as the DNDC (DeNitrification and DeComposition) model are useful tools when assessing the sustainability of agricultural management. Accuracy in soil temperature estimations is important as it regulates many important soil biogeochemical processes that lead to greenhouse gas emissions (GHG). The objective of this study was to account for the effects of snow cover in terms of the measured snow depth (mm of water), soil texture and crop management in temperate latitudes in order to improve the surface soil temperature mechanism in DNDC and thereby improve GHG predictions. The estimation of soil temperature driven by the thermal conductivity and heat capacity of the soil was improved by considering the soil texture under frozen and unfrozen conditions along with the effects of crop canopy and snow depth. Calibration of the developed model mechanisms was conducted using data from Alfred, ON under two contrasting soil textures (sandy loam vs. clay). Independent validation assessments were conducted using soil temperatures at different depths for contrasting managements for two field sites located in Canada (Guelph, ON and Glenlea, MB). The validation results indicated high model accuracy (R-2 > 0.90, EF >= 0.90, RMSE < 3.00 degrees C) in capturing the effects of management on soil temperature. These developments in soil heat transfer mechanism improved the performance of the model in estimating N2O emissions during spring thaw and provide a foundation for future studies aimed at improving simulations in DNDC for better representations of other biogeochemical processes. Crown Copyright (C) 2017 Published by Elsevier Ltd on behalf of IAgrE. All rights reserved.

The air quality modeling system RAMS (Regional Atmospheric Modeling System)-CMAQ (Models-3 Community Multi-scale Air Quality) is developed to simulate the aerosol optical depth (AOD) and aerosol direct forcing (DF). The aerosol-specific extinction, single scattering albedo, and asymmetry factor are parameterized based on Mie theory taking into account the aerosol size distribution, composition, refractive index, and water uptake of solution particles. A two-stream solar radiative model considers all gaseous molecular absorption, Rayleigh scattering, and aerosols and clouds. RAMS-CMAQ is applied to simulate all major aerosol concentrations (e.g., sulfate, nitrate, ammonium, organic carbon, black carbon, fine soil, and sea salt) and AOD and DF over East Asia in 2005. To evaluate its performance, the simulated AOD values were compared with ground-based in situ measurements. The comparison shows that RAMS-CMAQ performed well in most of the model domain and generally captured the observed variations. High AOD values (0.2-1.0) mainly appear in the Sichuan Basin as well as in central and southeastern China The geographic distribution of DF generally follows the AOD distribution patterns, and the DF at the top-of-the-atmosphere is less than -25 and -20 W m(-2) in clear-sky and all-sky over the Sichuan Basin. Both AOD and DF exhibit seasonal variations with lower values in July and higher ones in January. The DF could obviously be impacted by high cloud fractions.