Abstract. A recent development in the representation of aerosols in climate models is the realization that some components of organic aerosol (OA), emitted from biomass and biofuel burning, can have a significant contribution to shortwave radiation absorption in the atmosphere. The absorbing fraction of OA is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Atmosphere Model version 5 (CAM5), using a parameterization for BrC absorptivity described in Saleh et al. (2014). Nine-year experiments are run (2003–2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo and aerosol optical depth from the Aerosol Robotic Network (AERONET). This comparison reveals a model underestimation of single scattering albedo (SSA) in biomass burning regions for both default and BrC model runs, while a comparison between AERONET and the model absorption Ångström exponent shows a marked improvement with BrC implementation. Global annual average radiative effects are calculated due to aerosol–radiation interaction (REari; 0.13±0.01 W m−2) and aerosol–cloud interaction (REaci; 0.01±0.04 W m−2). REari is similar to other studies' estimations of BrC direct radiative effect, while REaci indicates a global reduction in low clouds due to the BrC semi-direct effect. The mechanisms for these physical changes are investigated and found to correspond with changes in global circulation patterns. Comparisons of BrC implementation approaches find that this implementation predicts a lower BrC REari in the Arctic regions than previous studies with CAM5. Implementation of BrC bleaching effect shows a significant reduction in REari (0.06±0.008 W m−2). Also, variations in OA density can lead to differences in REari and REaci, indicating the importance of specifying this property when estimating the BrC radiative effects and when comparing similar studies.

Marine stratocumulus clouds cover nearly one-quarter of the ocean surface and thus play an extremely important role in determining the global radiative balance. The semipermanent marine stratocumulus deck over the southeastern Atlantic Ocean is of particular interest, because of its interactions with seasonal biomass burning aerosols that are emitted in southern Africa. Understanding the impacts of biomass burning aerosols on stratocumulus clouds and the implications for regional and global radiative balance is still very limited. Previous studies have focused on assessing the magnitude of the warming caused by solar scattering and absorption by biomass burning aerosols over stratocumulus (the direct radiative effect) or cloud adjustments to the direct radiative effect (the semidirect effect). Here, using a nested modeling approach in conjunction with observations from multiple satellites, we demonstrate that cloud condensation nuclei activated from biomass burning aerosols entrained into the stratocumulus (the microphysical effect) can play a dominant role in determining the total radiative forcing at the top of the atmosphere, compared with their direct and semidirect radiative effects. Biomass burning aerosols over the region and period with heavy loadings can cause a substantial cooling (daily mean -8.05 W m), primarily as a result of clouds brightening by reducing the cloud droplet size (the Twomey effect) and secondarily through modulating the diurnal cycle of cloud liquid water path and coverage (the cloud lifetime effect). Our results highlight the importance of realistically representing the interactions of stratocumulus with biomass burning aerosols in global climate models in this region.

Abstract. The dust cycle is an important component of the Earth system and has been implemented in climate models and Earth system models (ESMs). An assessment of the dust cycle in these models is vital to address their strengths and weaknesses in simulating dust aerosol and its interactions with the Earth system and enhance the future model developments. This study presents a comprehensive evaluation of the global dust cycle in 15 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The various models are compared with each other and with an aerosol reanalysis as well as station observations. The results show that the global dust emission in these models varies by a factor of 4–5 for the same size range. The models generally agree with each other and observations in reproducing the “dust belt”, which extends from North Africa, the Middle East, Central and South Asia to East Asia, although they differ greatly in the spatial extent of this dust belt. The models also differ in other dust source regions such as North America and Australia. We suggest that the coupling of dust emission with dynamic vegetation can enlarge the range of simulated dust emission. For the removal process, all the models estimate that wet deposition is smaller than dry deposition and wet deposition accounts for 12 %–39 % of total deposition. The models also estimate that most (77 %–91 %) dust particles are deposited onto continents and 9 %–23 % of dust particles are deposited into oceans. Compared to the observations, most models reproduce the dust deposition and dust concentrations within a factor of 10 at most stations, but larger biases by more than a factor of 10 are also noted at specific regions and for certain models. These results highlight the need for further improvements of the dust cycle especially on dust emission in climate models.

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable‐resolution Community Earth System Model (VR‐CESM) with a high‐resolution (0.125°) refinement over the Rocky Mountain region. The VR‐CESM results are compared with observations, as well as CESM simulation at a quasi‐uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR‐CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR‐CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR‐CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR‐CESM. VR‐CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR‐CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR‐CESM captures the observed occurrence frequency and seasonal variation of rain‐on‐snow days and performs better than UNIF and CRCM5. These results demonstrate the VR‐CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

Dust emissions in climate and earth system models are associated with large uncertainties. These models often use the source erodibility (S) to constrain dust emissions and also lack explicit representations of the impact of surface roughness elements (SREs) on the threshold friction velocity (u*t). This study presents a process‐oriented evaluation of dust emission parameterizations in the Community Earth System Model (CESM) by applying the model to simulate a severe dust storm during 19–22 March 2010 in East Asia. Through numerical experiments, we assess the applicability of S and investigate the impact of SREs on dust emissions by implementing the roughness correction factor (fλ) to u*t. Simulation results are compared against the surface synoptic observations and station observations of dust concentrations. We found that the model can capture the main dust emission regions and reproduce the temporal‐spatial evolution of surface dust concentrations in Mongolia and northern China. With a geomorphic S (Sg), the model tends to produce excessive dust emissions over the low‐lying basins. Moreover, the high‐resolution Sg performs worse with “point sources” of strong dust emissions than the low‐resolution one. With the inclusion of fλ, total dust emissions are reduced by 24–34%, and the model reduces the overestimation of surface dust concentrations and improves their temporal variations over the vegetated regions. These results suggest that Sg may not be necessary when meteorology and land surface state are well simulated by the model and that fλ provides an important constraint on dust emissions through SREs.

Cloud phase and relative humidity (RH) distributions at −67° to 0°C over the Southern Ocean during austral summer are compared between in situ airborne observations and global climate simulations. A scale-aware comparison is conducted using horizontally averaged observations from 0.1 to 50 km. Cloud phase frequencies, RH distributions, and liquid mass fraction are found to be less affected by horizontal resolutions than liquid and ice water content (LWC and IWC, respectively), liquid and ice number concentrations (Ncliq and Ncice, respectively), and ice supersaturation (ISS) frequency. At −10° to 0°C, observations show 27%–34% and 17%–37% of liquid and mixed phases, while simulations show 60%–70% and 3%–4%, respectively. Simulations overestimate (underestimate) LWC and Ncliq in liquid (mixed) phase, overestimate Ncice in mixed phase, underestimate IWC in ice and mixed phases, and underestimate (overestimate) liquid mass fraction below (above) −5°C, indicating that observational constraints are needed for different cloud phases. RH frequently occurs at liquid saturation in liquid and mixed phases for all datasets, yet the observed RH in ice phase can deviate from liquid saturation by up to 20%–40% at −20° to 0°C, indicating that the model assumption of liquid saturation for coexisting ice and liquid is inaccurate for low liquid mass fractions (<0.1). Simulations lack RH variability for partial cloud fractions (0.1–0.9) and underestimate (overestimate) ISS frequency for cloud fraction <0.1 (≥0.6), implying that improving RH subgrid-scale parameterizations may be a viable path to account for small-scale processes that affect RH and cloud phase heterogeneities. Two sets of simulations (nudged and free-running) show very similar results (except for ISS frequency) regardless of sample sizes, corroborating the statistical robustness of the model–observation comparisons.

Dust aerosol plays an important role in the Earth System. As a natural aerosol, dust aerosol is often calculated interactively in global climate models and temporal variations of dust emission in the past century are far less constrained compared to those of anthropogenic aerosol emissions. Here we evaluate dust emission in East Asia simulated by 15 climate models participating in the Coupled Model Intercomparison Project Phase 5. The results show that none of the models can reproduce the observed decline of dust event frequency during 1961-2005 over East Asia. The models tend to simulate either much less decline or even increase of dust emission. The discrepancy is mainly ascribed to weaker or opposite trends of surface wind speeds and precipitation in the models. These results cast a doubt on the interpretation of long-term variations of dust-affected fields in climate models and highlight the need for further improvements of the models.Plain Language Summary Atmospheric aerosol is one of key factors that influence climate change.Aerosols include anthropogenic aerosols (such as sulfate aerosol and black carbon from fossil fuel burning) and natural aerosols (such as dust that is emitted by strong winds over bare soil). Climate models are important tools we use to predict the climate in the future, and the reliability of climate models lies in their ability to reproduce the change of climate system in the past. Here we examine the ability of climate models in reproducing the long-term change of dust storm frequency in East Asia. First, historical records of dust events show the dust activities decreased greatly during 1961 to 2005 over East Asia. Compared to this observation, current climate models are unable to reproduce the large decline of dust activities during 1961 to 2005. The reason is that climate models cannot capture the decrease of surface wind speed and increase of precipitation. These results imply that climate models may not represent well the change of meteorological elements (e.g., temperature and clouds) that will be affected by dust. Our results highlight urgent need to improve the performance of climate models in simulating long-term dust change.

Abstract. Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD) simulated by the Community Earth System Model version 1 (CESM1) and version 2 (CESM2), the Energy Exascale Earth System Model version 1 (E3SMv1), and the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) against satellite retrievals from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multi-angle Imaging SpectroRadiometer (MISR). We find that CESM1, CESM2, and E3SMv1 underestimate dust transport to remote regions. E3SMv1 performs better than CESM1 and CESM2 in simulating dust transport and the northern hemispheric DOD due to its higher mass fraction of fine dust. CESM2 performs the worst in the Northern Hemisphere due to its lower dust emission than in the other two models but has a better dust simulation over the Southern Ocean due to the overestimation of dust emission in the Southern Hemisphere. DOD from MERRA-2 agrees well with CALIOP DOD in remote regions due to its higher mass fraction of fine dust and the assimilation of aerosol optical depth. The large disagreements in the dust extinction profiles and DOD among CALIOP, MODIS, and MISR retrievals make the model evaluation of dust spatial distributions challenging. Our study indicates the importance of representing dust emission, dry/wet deposition, and size distribution in GCMs in correctly simulating dust spatiotemporal distributions.