Dust emissions related to anthropogenic activities (i.e., anthropogenic dust (AD)) is not represented in most global climate models and its radiative impact remains unassessed. In this study, we develop a new and physically based method to parameterize AD emission based on the DOE’s Energy Exascale Earth System Model version 1 (E3SMv1). This method relates AD emission to the crop land use fraction in the E3SMv1 land component. Major AD sources simulated by our parameterization include those over Central America, the Sahel, North India, and North China. The annual averaged AD emission is 567 Tg yr-1 in present-day (year 2000), which contributes to 13.3 % of total dust emission. Model evaluation against satellite and ground-based observations shows that the new parameterization can represent AD emissions and global dust cycle reasonably well. We find that the total dust emission increases by 13 % (495 Tg yr-1) from 1850 to 2000 mainly due to the cropland land use fraction changes, which induces a net dust direct effective radiative forcing of -0.041 W m-2 at top of the atmosphere. This AD-induced cooling exceeds 10% of the total anthropogenic aerosol direct effective radiative forcing from 1750 to 2014 estimated by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Our findings indicate an important role of AD in the regional and global climate changes, which should be included in future climate change assessments.

This study evaluates high-latitude stratiform mixed-phase clouds (SMPC) in the atmosphere model of the newly released Energy Exascale Earth System Model version 2 (EAMv2) by utilizing one-year-long ground-based remote sensing measurements from the U.S. Department of Energy Atmospheric Radiation and Measurement (ARM) Program. A nudging approach is applied to model simulations for a better comparison with the ARM observations. Observed and modeled SMPCs are collocated to evaluate their macro- and microphysical properties at the ARM North Slope of Alaska (NSA) site in the Arctic and the McMurdo (AWR) site in the Antarctic. We found that EAMv2 overestimates (underestimates) SMPC frequency of occurrence at the NSA (AWR) site nearly all year round. However, the model captures the observed larger cloud frequency of occurrence at the NSA site. For collocated SMPCs, the annual statistics of observed cloud macrophysics are generally reproduced at the NSA site, while at the AWR site, there are larger biases. Compared to the AWR site, the lower cloud boundaries and the warmer cloud top temperature observed at NSA are well simulated. On the other hand, simulated cloud phases are substantially biased at each location. The model largely overestimates liquid water path at NSA, whereas it is frequently underestimated at AWR. Meanwhile, the simulated ice water path is underestimated at NSA, but at AWR, it is comparable to observations. As a result, the observed hemispheric difference in cloud phase partitioning is misrepresented in EAMv2. This study implies that continuous improvement in cloud microphysics is needed for high-latitude mixed-phase clouds.

Snow and ice albedo reduction due to deposition of absorbing particles (i.e., snow darkening effect (SDE)) warms the Earth system and is largely attributed to black carbon (BC) and dust. Absorbing organic aerosol (BrC) also contributes to SDE but has received less attention due to uncertainty and challenges in model representation. This work incorporates the SDE of absorbing organic aerosol (BrC) from biomass burning and biofuel sources into the Snow Ice and Aerosol Radiative (SNICAR) model within a variant of the Community Earth System Model (CESM). Additionally, 12 different emission regions of BrC and BC from biomass burning and biofuel sources are tagged to quantify the relative contribution to global and regional SDE. BrC global SDE (0.021–0.056 Wm-2) is larger than other model estimates, corresponding to 37%–98% of the SDE from BC. When compared to observations, BrC simulations have a range in median bias (-2.5%–+21%), with better agreement in the simulations that include BrC photochemical bleaching. The largest relative contributions to global BrC SDE are traced to Northern Asia (23%–31%), Southeast Asia (16%–21%), and South Africa (13%–17%). Transport from Southeast Asia contributes nearly half of the regional BrC SDE in Antarctica (0.084–0.3 Wm-2), which is the largest regional input to global BrC SDE. Lower latitude BrC SDE is correlated with snowmelt, in-snow BrC concentrations, and snow cover fraction, while polar BrC SDE is correlated with surface insolation and snowmelt. This indicates the importance of in-snow processes and snow feedbacks on modeled BrC SDE.

Measured ice number concentrations are often much higher than the number concentrations of ice nucleating particles (INPs) in moderately cold mixed-phase clouds, suggesting the potential importance of secondary ice nucleation (SIP). However, the occurrence frequency and importance of SIP relative to primary ice nucleation for ice formation and mixed-phase cloud properties are largely unknown. Representing the SIP processes in weather and climate models is equally challenging. In this study, we present a process-level understanding of SIP in high-latitude mixed-phase clouds based on integrated model-observational analyses of the NSF SOCRATES aircraft and DOE ARM MARCUS ship-borne data. We run the Community Earth System Model version 2 (CESM2) nudged towards the MERRA2 Reanalysis and output the modeled clouds and aerosols along the aircraft flight and ship tracks for direct model-observation comparisons. We found that CESM2 with a physical representation of SIP processes (e.g., ice-ice collisional break-up, droplet shattering during rain freezing) better capture the observed ice crystal number concentrations (ICNCs) and cloud properties. SIP often dominants the ice formation in the moderately cold mixed-phase clouds, and transforms ~30% of pure liquid-phase clouds simulated in the model into mixed-phase clouds. We also compare modeled ice enhancement ratio due to SIP to ICNC and INP number concentrations observed during SOCRATES and MARCUS.

Significant changes are found in the modeled phase partitioning of Arctic mixed-phase clouds in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) compared to its predecessor, the Community Atmosphere Model version 5 (CAM5). In this study, we aim to understand how the changes in modeled mixed-phase cloud properties are attributed to the updates made in the EAMv1 physical parameterizations. Impacts of the Classical Nucleation Theory (CNT) ice nucleation scheme, the Cloud Layer Unified By Binormals (CLUBB) parameterization, and updated Morrison and Gettelman microphysical scheme (MG2) are examined. Sensitivity experiments using the short-term hindcast approach are performed to isolate the impact of these new features on simulated mixed-phase clouds. Results are compared to the DOE’s Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We find that mixed-phase clouds simulated in EAMv1 are overly dominated by supercooled liquid and cloud ice water is substantially underestimated. The individual change of physical parameterizations is found to decrease cloud ice water mass mixing ratio in EAMv1 simulated single-layer mixed-phase clouds. A budget analysis of detailed cloud microphysical processes suggests that the lack of ice particles that participate in the mass growth processes strongly inhibits the mass mixing ratio of cloud ice. The insufficient heterogeneous ice nucleation at temperatures warmer than -15C in CNT and the negligible ice processes in CLUBB are primarily responsible for the significant underestimation of cloud ice water content in the Arctic single-layer mixed-phase clouds.

Measured ice crystal number concentrations are often orders of magnitude higher than the number concentrations of ice nucleating particles, indicating the existence of secondary ice production (SIP) in clouds. Here, we present the first study to examine the global impacts of SIP through droplet shattering during freezing of rain, ice-ice collision fragmentation, and rime splintering, using a global climate model. Our results show that SIP happens pretty uniformly in the two hemispheres and dominates the ice formation in the moderately cold clouds with temperatures warmer than -15℃. SIP decreases the global averaged liquid water path by –14.6 g m–2 (–22%), increases the global averaged ice water path by 8.7 g m–2 (23%), improving the model agreement with observations. SIP changes the shortwave, longwave, and net cloud forcing by 2.1, –1.0, and 1.1 W m–2, respectively, highlighting the importance of SIP on cloud properties on the global scale.

This study performs a comprehensive evaluation of the simulated cloud phase in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) atmosphere model version 2 (EAMv2) and version 1 (EAMv1). Enabled by the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) simulator, EAMv2 and EAMv1 predicted cloud phase is compared against the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) at high latitudes where mixed-phase clouds are prevalent. Our results indicate that the underestimation of cloud ice in simulated high-latitude mixed-phase clouds in EAMv1 has been significantly reduced in EAMv2. The increased ice clouds in the Arctic mainly result from the modification on the WBF (Wegner-Bergeron-Findeisen) process in EAMv2. The impact of the modified WBF process is moderately compensated by the low limit of cloud droplet number concentration (CDNC) in cloud microphysics and the new dCAPE_ULL trigger used in deep convection in EAMv2. Moreover, it is found that the new trigger largely contributes to the better cloud phase simulation over the Norwegian Sea and Barents Sea in the Arctic and the Southern Ocean where large errors are found in EAMv1. However, errors in simulated cloud phase in EAMv1, such as the overestimation of supercooled liquid clouds near the surface in both hemispheres and the underestimation of ice clouds over Antarctica, persist in EAMv2. This study highlights the impact of deep convection parameterizations, which has not been paid much attention, on high-latitude mixed-phase clouds, and the importance of continuous improvement of cloud microphysics in climate models for accurately representing mixed-phase clouds.

The dust aerosols are a major type of aerosol over the Tibetan Plateau (TP) and influence climate at local to regional scales through their effects on thermal radiation and snow-albedo feedback. Based on the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) aerosol dataset, we report an increase of 34% in the atmospheric dust in the high troposphere over the TP during the spring season in the 2000s in comparison to the 1990s. This result is supported by an increase of 157% (46%) in the dust deposition flux in the Mugagangqiong (Tanggula) ice cores and an increase of 69% in the Aerosol Index (AI) from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS), as well as by increases of simulated dust aerosols over the TP derived from the Community Earth System Model (CESM) and models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The increased atmospheric dust over the TP is caused in two aspects: (1) there was a higher dust emission over the Middle East during the 2000s than during the 1990s, which is explained by less precipitation and 25.8% higher in cyclone frequency over the Middle East. The increased cyclones uplift more dust from the surface over the Middle East to the central Asia in the middle troposphere. (2) Enhanced mid-latitude zonal winds help transport more dust in the middle troposphere from the central Asia to the Northwest China and thereafter an increase in northerly winds over Northwest China propels dust southward to the TP.

Nitrate aerosol plays an important role in affecting regional air quality as well as Earth’s climate. However, it is not well represented or even neglected in many global climate models. In this study, we couple the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module with the four-mode version of the Modal Aerosol Module (MAM4) in DOE’s Energy Exascale Earth System Model version 2 (E3SMv2) to treat nitrate aerosol and its radiative effects. We find that nitrate aerosol simulated by E3SMv2-MAM4-MOSAIC is sensitive to the treatment of gaseous HNO3 transfer to/from interstitial particles related to accommodation coefficients of HNO3 (αHNO3) on dust and non-dust particles. We compare three different treatments of HNO3 transfer: 1) a treatment (MTC_SLOW) that uses a low αHNO3 in the mass transfer coefficient (MTC) calculation; 2) a dust-weighted MTC treatment (MTC_WGT) that uses a high αHNO3 on non-dust particles; and 3) a dust-weighted MTC treatment that also splits coarse mode aerosols into the coarse dust and sea salt sub-modes in MOSAIC (MTC_SPLC). MTC_WGT and MTC_SPLC increase the global annual mean (2005-2014) nitrate burden from 0.096 (MTC_SLOW) to 0.237 and 0.185 Tg N, respectively, mostly in the coarse mode. They also produce stronger nitrate direct radiative forcing (–0.048 and –0.051 W m–2, respectively) and indirect forcing (–0.33 and –0.35 W m–2, respectively) than MTC_SLOW (–0.021 and –0.24 W m–2). All three treatments overestimate nitrate surface concentrations compared with ground-based observations. MTC_WGT and MTC_SPLC improve the vertical profiles of nitrate concentrations against aircraft measurements below 400 hPa.