Abstract. Fires including peatland burning in Southeast Asia have become a major concern to the general public as well as governments in the region. This is because aerosols emitted from such fires can cause persistent haze events under certain weather conditions in downwind locations, degrading visibility and causing human health issues. In order to improve our understanding of the spatiotemporal coverage and influence of biomass burning aerosols in Southeast Asia, we have used surface visibility and particulate matter concentration observations, supplemented by decade-long (2003 to 2014) simulations using the Weather Research and Forecasting (WRF) model with a fire aerosol module, driven by high-resolution biomass burning emission inventories. We find that in the past decade, fire aerosols are responsible for nearly all events with very low visibility (< 7 km). Fire aerosols alone are also responsible for a substantial fraction of low-visibility events (visibility  < 10 km) in the major metropolitan areas of Southeast Asia: up to 39 % in Bangkok, 36 % in Kuala Lumpur, and 34 % in Singapore. Biomass burning in mainland Southeast Asia accounts for the largest contribution to total fire-produced PM2.5 in Bangkok (99 %), while biomass burning in Sumatra is a major contributor to fire-produced PM2.5 in Kuala Lumpur (50 %) and Singapore (41 %). To examine the general situation across the region, we have further defined and derived a new integrated metric for 50 cities of the Association of Southeast Asian Nations (ASEAN): the haze exposure day (HED), which measures the annual exposure days of these cities to low visibility (< 10 km) caused by particulate matter pollution. It is shown that HEDs have increased steadily in the past decade across cities with both high and low populations. Fire events alone are found to be responsible for up to about half of the total HEDs. Our results suggest that in order to improve the overall air quality in Southeast Asia, mitigation policies targeting both biomass burning and fossil fuel burning sources need to be implemented.

Abstract. A source-oriented version of the Weather Research and Forecasting model with chemistry (SOWC, hereinafter) was developed. SOWC separately tracks primary particles with different hygroscopic properties rather than instantaneously combining them into an internal mixture. This approach avoids artificially mixing light absorbing black + brown carbon particles with materials such as sulfate that would encourage the formation of additional coatings. Source-oriented particles undergo coagulation and gas-particle conversion, but these processes are considered in a dynamic framework that realistically "ages" primary particles over hours and days in the atmosphere. SOWC more realistically predicts radiative feedbacks from anthropogenic aerosols compared to models that make internal mixing or other artificial mixing assumptions. A three-week stagnation episode (15 December 2000 to 6 January 2001) in the San Joaquin Valley (SJV) during the California Regional PM10 / PM2.5 Air Quality Study (CRPAQS) was chosen for the initial application of the new modeling system. Primary particles emitted from diesel engines, wood smoke, high-sulfur fuel combustion, food cooking, and other anthropogenic sources were tracked separately throughout the simulation as they aged in the atmosphere. Differences were identified between predictions from the source oriented vs. the internally mixed representation of particles with meteorological feedbacks in WRF/Chem for a number of meteorological parameters: aerosol extinction coefficients, downward shortwave flux, planetary boundary layer depth, and primary and secondary particulate matter concentrations. Comparisons with observations show that SOWC predicts particle scattering coefficients more accurately than the internally mixed model. Downward shortwave radiation predicted by SOWC is enhanced by ~1% at ground level chiefly because diesel engine particles in the source-oriented mixture are not artificially coated with material that increases their absorption efficiency. The extinction coefficient predicted by SOWC is reduced by an average of 0.012 km−1 (4.8%) in the SJV with a maximum reduction of ~0.2 km−1. Planetary boundary layer (PBL) height is increased by an average of 5.2 m (1.5%) with a~maximum of ~100 m in the SJV. Particulate matter concentrations predicted by SOWC are 2.23 μg m−3 (3.8%) lower than the average by the internally mixed version of the same model in the SJV because increased solar radiation at the ground increases atmospheric mixing. The changes in predicted meteorological parameters and particle concentrations identified in the current study stem from the mixing state of black carbon. The source-oriented model representation with realistic aging processes predicts that hydrophobic diesel engine particles remain largely uncoated over the +7 day simulation period, while the internal mixture model representation predicts significant accumulation of secondary nitrate and water on diesel engine particles. Similar results will likely be found in any air pollution stagnation episode that is characterized by significant particulate nitrate production. Future work should consider episodes where coatings are predominantly sulfate and/or secondary organic aerosol.

Abstract. Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years. Widespread biomass burning occurrences and particulate pollutants from human activities other than biomass burning play important roles in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus nonfire (including fossil fuel combustion, and road dust, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and are driven by emissions from (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. The model results reveal that 39 % of observed low-visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. Analysis of an 24 h PM 2.5 air quality index (AQI) indicates that the case with coexisting fire and non-fire PM 2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 to 34 %. The premature mortality in major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ∼ 4110 per year in 2002 to ∼ 6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore is also explored in this study. All of these results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia needs to consider controlling emissions from non-fire anthropogenic sources.

Abstract. Open-burning fires play an important role in the earth's climate system. In addition to contributing a substantial fraction of global emissions of carbon dioxide, they are a major source of atmospheric aerosols containing organic carbon, black carbon, and sulfate. These "fire aerosols" can influence the climate via direct and indirect radiative effects. In this study, we investigate these radiative effects and the hydrological fast response using the Community Atmosphere Model version 5 (CAM5). Emissions of fire aerosols exert a global mean net radiative effect of −1.0 W m −2 , dominated by the cloud shortwave response to organic carbon aerosol. The net radiative effect is particularly strong over boreal regions. Conventionally, many climate modelling studies have used an interannually invariant monthly climatology of emissions of fire aerosols. However, by comparing simulations using interannually varying emissions vs. interannually invariant emissions, we find that ignoring the interannual variability of the emissions can lead to systematic overestimation of the strength of the net radiative effect of the fire aerosols. Globally, the overestimation is +23 % (−0.2 W m −2 ). Regionally, the overestimation can be substantially larger. For example, over Australia and New Zealand the overestimation is +58 % (−1.2 W m −2 ), while over Boreal Asia the overestimation is +43 % (−1.9 W m −2 ). The systematic overestimation of the net radiative effect of the fire aerosols is likely due to the non-linear influence of aerosols on clouds. However, ignoring interannual variability in the emissions does not appear to significantly impact the hydrological fast response. In order to improve understanding of the climate system, we need to take into account the interannual variability of aerosol emissions.

This study evaluates the impact of dust–radiation–cloud interactions on the development of a mesoscale convective system (MCS) by comparing numerical experiments run with and without dust–radiation and/or dust–cloud interactions. An MCS that developed over North Africa on 4–6 July 2010 is used as a case study. The CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites passed over the center of the MCS after it reached maturity, providing valuable profiles of aerosol backscatter and cloud information for model verification. The model best reproduces the MCS’s observed cloud structure and morphology when both dust–radiation and dust–cloud interactions are included. Our results indicate that the dust–radiation effect has a far greater influence on the MCS’s development than the dust-cloud effect. Results show that the dust-radiative effect, both with and without the dust–cloud interaction, briefly delays the MCS’s formation but ultimately produces a stronger storm with a more extensive anvil cloud. This is caused by dust–radiation-induced changes to the MCS’s environment. The impact of the dust–cloud effect on the MCS, on the other hand, is greatly affected by the presence of the dust–radiation interaction. The dust–cloud effect alone slows initial cloud development but enhances heterogeneous ice nucleation and extends cloud lifetime. When the dust–radiation interaction is added, increased transport of dust into the upper portions of the storm—due to a dust–radiation-driven increase in convective intensity—allows dust–cloud processes to more significantly enhance heterogeneous freezing activity earlier in the storm’s development, increasing updraft strength, hydrometeor growth (particularly for ice particles), and rainfall.

The low cloud bias in global climate models (GCMs) remains an unsolved problem. Coarse vertical resolution in GCMs has been suggested to be a significant cause of low cloud bias because planetary boundary layer parameterizations cannot resolve sharp temperature and moisture gradients often found at the top of subtropical stratocumulus layers. This work aims to ameliorate the low cloud problem by implementing a new computational method, the Framework for Improvement by Vertical Enhancement (FIVE), into the Energy Exascale Earth System Model (E3SM). Three physics schemes representing microphysics, radiation, and turbulence as well as vertical advection are interfaced to vertically enhanced physics (VEP), which allows for these processes to be computed on a higher vertical resolution grid compared to the rest of the E3SM model. We demonstrate the better representation of subtropical boundary layer clouds with FIVE while limiting additional computational cost from the increased number of levels. When the vertical resolution approaches the large eddy simulation‐like vertical resolution in VEP, the climatological low cloud amount shows a significant increase of more than 30% in the southeastern Pacific Ocean. Using FIVE to improve the representation of low‐level clouds does not come with any negative side effects associated with the simulation of mid‐ and high‐level cloud and precipitation, that can occur when running the full model at higher vertical resolution.

High vertical resolution in the lower troposphere is a crucial ingredient to improve marine stratocumulus (Sc) in GCMs.• These simulations are expensive and require time step adjustment, which intro-10 duces sensitivities. 11• Vertical resolution alone cannot improve coastal Sc, likely concurrent increases in 12 horizontal resolution are needed.

Aerosols emitted from fossil fuel burning can cause air quality and human health issues. In this sensitivity study, we examine the impact of fossil fuel aerosols on air quality in Southeast Asia under five different hypothetical fuel consumption scenarios. These scenarios reflect air pollutant outcomes of implementations of certain idealized policies in the power generation, industry, and residential sectors. Analyses based on comparison among the modeling results from these scenarios reveal the sectors that should be targeted by air pollution mitigation policy. The results reveal that in Southeast Asia, sulfate could be decreased by 25% if coal were to be replaced by natural gas in the power generation and industry sectors. Black carbon concentration would reduce 42% overall if biofuel were replaced by natural gas in the residential sector. Shipping emissions are especially critical for the urban air quality in Singapore: fine particular matters (PM 2.5 ) could be dramatically cut by 69% in Singapore by merely eliminating shipping emissions.