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At least 1,063 records · Page 59

Separating radiative forcing by aerosol–cloud interactions and rapid cloud adjustments in the ECHAM–HAMMOZ aerosol–climate model using the method of partial radiative perturbations

Using the method of offline radiative transfer modeling within the partial radiative perturbation (PRP) approach, the effective radiative forcing by aerosol–cloud interactions (ERF aci ) in the ECHAM–HAMMOZ aerosol climate model is decomposed into a radiative forcing by anthropogenic cloud droplet number change and adjustments of the liquid water path and cloud fraction.The simulated radiative forcing by anthropogenic cloud droplet number change and liquid water path adjustment are of approximately equal magnitude at –0.52 and –0.53 W m –2 , respectively, while the cloud-fraction adjustment is somewhat weaker at –0.31 W m –2 (constituting 38 %, 39 %, and 23 %of the total ERFaci, respectively); geographically, all three ERF aci components in the simulation peak over China, the subtropical eastern ocean boundaries,the northern Atlantic and Pacific oceans, Europe, and eastern North America (in order of prominence). Spatial correlations indicate that the temporal-mean liquid water path adjustment is proportional to the temporal-mean radiative forcing, while the relationship between cloud-fraction adjustment and radiative forcing is less direct. While the estimate of warm-cloud ERF aci is relatively insensitive to the treatment of ice and mixed-phase cloud overlying warm cloud, there are indications that more restrictive treatments of ice in the column result in a low bias in the estimated magnitude of the liquid water path adjustment and a high bias in the estimated magnitude of the droplet number forcing. Since the present work is the first PRP decomposition of the aerosol effective radiative forcing into radiative forcing and rapid cloud adjustments, idealized experiments are conducted to provide evidence that the PRP results are accurate. The experiments show that using low-frequency(daily or monthly) time-averaged model output of the cloud property fields underestimates the ERF, but 3-hourly mean output is sufficiently frequent.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of the boundary layer energy fluxes to forcing parameters in a simple climate model

Winter and summer surface temperatures and time-averaged boundary layer energy fluxes are calculated by utilizing the Saltzman-Ashe parameterization for boundary layer fluxes in a two-level static model. The results are found to agree with observed patterns. Within the framework of this simple model, sensitivity analyses of the time-averaged boundary layer energy fluxes are conducted. Based on these results some of the forcing parameters (such as the subsurface temperature, cloud cover, surface albedo, etc.) are arranged in a hierarchical order of importance. A generalized method of sensitivity analysis is also suggested.

Rao, M. S.↗

Satellite estimates of ocean-air heat fluxes during cold air outbreaks

A method for estimating the heat and moisture fluxes of coastal waters using the cloud free path, the sea surface temperature, and the saturation water vapor mixing ratio is presented. Generalized nomograms for the surface sensible and latent heat fluxes are developed using the Stage and Businger (1981) mixed-layer model. The fluxes are found to be slightly dependent on wind speed. The results are found to be applicable to any path within the cloud-free region, with heat fluxes obtainable by multiplication of the mean heating by the mean wind speed in the boundary layer. Higher stability causes lowered heating. It is shown that the latent heat flux is linear. Applications of the method to lake-effect snowstorms and for verification of boundary-layer models are indicated.

Chou, S.-H.↗

Photochemical ozone production in tropical squall line convection during NASA Global Tropospheric Experiment/Amazon Boundary Layer Experiment 2A

The role of convection was examined in trace gas transport and ozone production in a tropical dry season squall line sampled on August 3, 1985, during NASA Global Tropospheric Experiment/Amazon Boundary Layer Experiment 2A (NASA GTE/ABLE 2A) in Amazonia, Brazil. Two types of analyses were performed. Transient effects within the cloud are examined with a combination of two-dimensional cloud and one-dimensional photochemical modeling. Tracer analyses using the cloud model wind fields yield a series of cross sections of NO(x), CO, and O3 distribution during the lifetime of the cloud; these fields are used in the photochemical model to compute the net rate of O3 production. At noon, when the cloud was mature, the instantaneous ozone production potential in the cloud is between 50 and 60 percent less than in no-cloud conditions due to reduced photolysis and cloud scavenging of radicals. Analysis of cloud inflows and outflows is used to differentiate between air that is undisturbed and air that has been modified by the storm. These profiles are used in the photochemical model to examine the aftereffects of convective redistribution in the 24-hour period following the storm. Total tropospheric column O3 production changed little due to convection because so little NO(x) was available in the lower troposphere. However, the integrated O3 production potential in the 5- to 13-km layer changed from net destruction to net production as a result of the convection. The conditions of the August 3, 1985, event may be typical of the early part of the dry season in Amazonia, when only minimal amounts of pollution from biomass burning have been transported into the region.

Pickering, Kenneth E.↗

Numerical modeling of coronal mass ejections based on various pre-event model atmospheres

We examine how the initial state (pre-event corona) affects the numerical MHD simulation for a coronal mass ejection (CME). Earlier simulations based on a pre-event corona with a homogeneous density and temperature distribution at lower boundary (i.e. solar surface) have been used to analyze the role of streamer properties in determining the characteristics of loop-like transients. The present paper extends these studies to show how a broader class of global coronal properties leads not only to different types of CME's, but also modifies the adjacent quiet corona and/or coronal holes. We consider four pre-event coronal cases: (1) Constant boundary conditions and a polytropic gas with gamma = 1.05; (2) Non-constant (latitude dependent) boundary conditions and a polytropic gas with gamma = 1.05; (3) Constant boundary conditions with a volumetric energy source and gamma = 1.67; (4) Non-constant (latitude dependent) boundary conditions with a volumetric energy source and gamma = 1.67. In all models, the pre-event magnetic fields separate the corona into closed field regions (streamers) and open field regions. The CME's initiation is simulated by introducing at the base of the corona, within the streamer region, a standard pressure pulse and velocity change. Boundary values are determined using MHD characteristic theory. The simulations show how different CME's, including loop-like transients, clouds, and bright rays, might occur. There are significant new features in comparison to published results. We conclude that the pre-event corona is a crucial factor in dictating CME's properties.

Suess, S. T.↗

UVI Auroral Observations During the January 10, 1997 Magnetic Cloud Event

Solar wind IMF and plasma conditions surrounding the January 10-11 magnetic cloud event provided very interesting observations relating to magnetospheric and ionospheric processes. Prior to the arrival of the magnetic cloud a shock front followed by abrupt swings in the IMF orientation were observed by the Wind spacecraft at about 100 Re upstream. The Polar Ultraviolet Imager (UVI) near apogee over the northern hemisphere recorded the encounter of the shock with the magnetosphere. Enhancement of dayside precipitation around noon MLT and progression of the enhancement along dawn and dusk flanks of the oval culminating in a very localized pseudo onset near midnight MLT were observed. During the following mainly northward IMF the polar cap region was the site of multiple sunward aligned arcs and curled arc structures that persisted until the IMF turned rapidly southward. While the IMF remained southward the polar cap cleared of arc structures and expanded, and the auroral oval became very thin. No substorms were observed for at least 25 minutes after the following northward turning contrary to what might be expected on the basis of recent reports of substorm initiation by northward turning of the IMF. These observations and others during the magnetic cloud event provide a clear case study of the effect of the solar wind on dayside precipitation, thickness of the boundary layer, magnetosphere-polar cap magnetic topology and sources of the polar cap precipitation, and triggering of substorms. These issues will be discussed along with the presentation of the UVI auroral observations and solar wind measurements.

Brittnacher, M. J.↗

Airborne High Spectral Resolution Lidar-2 Measurements of Enhanced Depolarization in Marine Aerosols

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA EVS-3 Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed enhanced particulate linear depolarization associated with aerosols within the marine boundary layer. These HSRL-2 observations were acquired off the east coast of the United States in February and March 2020 when this lidar was deployed on the NASA LaRC UC-12 aircraft. HSRL-2 measured profiles of aerosol backscattering, extinction,and depolarization at 355 and 532nm and aerosol backscattering and depolarization at 1064nm. Typically HSRL-2 measures low (<5%) linear particulate depolarization associated with marine sea salt aerosols. However, during several ACTIVATE flights, particularly those that occurred with outbreaks of cold, dry air, linear particulate depolarization exceeded 15-20% (532nm) for aerosols within a few hundred meters above the surface. These high values indicated that these particles were nonspherical. Elevated depolarization values were also observed at 355 and 1064 nm. HSRL-2 measured aerosol extinction/backscatter ratio (“lidar ratio”) values around 20-25 sr (355 and 532 nm) that are typically associated with sea salt particles. Coincident measurements of relative humidity from dropsondes released from the UC-12and in situ Diode Laser Hygrometer (DLH) measurements flown on the NASA HU-25 aircraft showed that highest depolarization values of these nonspherical particles were found when the relative humidity (RH)was below 50-60%.These lidar observations of elevated depolarization associated with sea salt aerosol are consistent with previous lidar measurements of sea salt aerosols in dry conditions. We discuss these HSRL-2 measurements also in the context of coincident airborne in situ measurements of particle size and composition acquired on the HU-25 aircraft. We also found that CALIOP satellite measurements observed elevated depolarization during some similar cold air outbreaks. In such cases, the operational CALIOP algorithms attributed the elevated depolarization to nonspherical dust particles rather than the more likely scenario of nonspherical sea salt particles associated with low RH.

aerosols↗

Numerical Analysis Using WRF-SBM for the Cloud Microphysical Structures in the C3VP Field Campaign: Impacts of Supercooled Droplets and Resultant Riming on Snow Microphysics

Two distinct snowfall events are observed over the region near the Great Lakes during 19-23 January 2007 under the intensive measurement campaign of the Canadian CloudSat/CALIPSO validation project (C3VP). These events are numerically investigated using the Weather Research and Forecasting model coupled with a spectral bin microphysics (WRF-SBM) scheme that allows a smooth calculation of riming process by predicting the rimed mass fraction on snow aggregates. The fundamental structures of the observed two snowfall systems are distinctly characterized by a localized intense lake-effect snowstorm in one case and a widely distributed moderate snowfall by the synoptic-scale system in another case. Furthermore, the observed microphysical structures are distinguished by differences in bulk density of solid-phase particles, which are probably linked to the presence or absence of supercooled droplets. The WRF-SBM coupled with Goddard Satellite Data Simulator Unit (G-SDSU) has successfully simulated these distinctive structures in the three-dimensional weather prediction run with a horizontal resolution of 1 km. In particular, riming on snow aggregates by supercooled droplets is considered to be of importance in reproducing the specialized microphysical structures in the case studies. Additional sensitivity tests for the lake-effect snowstorm case are conducted utilizing different planetary boundary layer (PBL) models or the same SBM but without the riming process. The PBL process has a large impact on determining the cloud microphysical structure of the lake-effect snowstorm as well as the surface precipitation pattern, whereas the riming process has little influence on the surface precipitation because of the small height of the system.

lake-effect↗

Assessment of Cloud Fraction Derived from a New Geostationary Satellite Cloud Retrieval Algorithm for CERES and Progress Towards Cross-platform Continuity

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has produced long-term records of top-of-atmosphere (TOA) and surface irradiances for detecting changes in the Earth’s radiation budget and advancing understanding of how clouds contribute to those changes. Accurate characterization of the spatial and temporal distributions of clouds are a critical component for producing CERES datasets. The CERES Cloud Working Group (CWG) derives cloud properties from both geostationary (GEO) and low-Earth orbit (LEO) satellite sensors in order to provide complete global coverage at hourly temporal resolution. However, the use of multiple sensors to provide this spatiotemporal coverage throughout a long-term record presents some challenges, because the various sensors generally have different spectral band characteristics (e.g., spectral band width and response) and spatial resolution. These differences can result in spatial artifacts at the coverage boundary between two sensors or temporal artifacts when one sensor replaces another in the record. For the upcoming Edition 5 release of CERES products, the CWG is developing cloud retrieval algorithms which utilize only spectral bands common to most modern passive satellite radiometers and account for differences in spectral width and response. The goal with this approach is to provide global cloud properties for CERES with greater cross-platform consistency than the previous Edition 4 products and thus mitigate artifacts which are evident at the interface of two sensors. This study focuses on retrieval of total cloud fraction from various GEO sensors, and we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to assess the accuracy of total cloud fraction derived from the various sensors. The Edition 5 cloud mask algorithm depends on estimates of cloud-free TOA spectral radiances to differentiate clear and cloudy conditions, and CALIOP is used to assess the accuracy of those estimates when cloud-free conditions are indeed observed.

CALIOP↗

Exploring Sources of Surface Bias in HRRR Using New York State Mesonet

In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.

54 ENVIRONMENTAL SCIENCES↗

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Study for Forecasting Variables of WRF-Solar Using a Tangent Linear Approach

Integrating solar generation in recent years has highlighted the need for improved accuracy in predicting solar power. Confidence in solar power forecasting can be achieved by designing an ensemble that provides reliable probabilistic information for solar radiation with reduced uncertainty and error. Ideally, ensemble members are created through the optimized perturbation of the initial conditions in numerical weather prediction (NWP) models. Tangent linear models are capable of efficiently investigating the sensitivity of solar radiation to model input parameters because they do not require individual perturbation of each variable. This sensitivity study using tangent linear models provide us the capability to identify the right variables to perturb in an ensemble prediction system. In this study, we developed tangent linear models for WRF-Solar modules that directly impact the computation of solar radiation and the simulation of cloud formation and dissipation including the Fast All-sky Model for Solar Applications (FARMS), the Noah land surface model (LSM), the Thompson microphysics, the Mello-Yamada-Nakanishi-Niino (MYNN) boundary layer parameterization, and the Deng scheme for a shallow-convection parameterization. A sensitivity analysis was conducted under various scenarios based on satellite observations and model simulations from the National Solar Radiation Data Base (NSRDB) and WRF-Solar, respectively. Critical forecasting variables that are highly sensitive to the forecasting of global horizontal irradiance (GHI), direct normal irradiance (DNI), cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes were determined using the relevant WRF-Solar module. This study will be used as a guidance on future research leading to high-quality probabilistic solar forecasting. In this presentation, we discuss the validation of tangent linear approach for WRF-Solar modules and illustrate how the sensitivity results are valuable in the improvement of probabilistic solar prediction.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ensemble formulation of surface fluxes and improvement in evapotranspiration and cloud parameterizations in a GCM

The influence of some modifications to the parameters of the current general circulation model (GCM) is investigated. The aim of the modifications was to eliminate strong occasional bursts of oscillations in planetary boundary layer (PBL) fluxes. Smoothly varying bulk aerodynamic friction and heat transport coefficients were found by ensemble averaging of the PBL fluxes in the current GCM. A comparison was performed of the simulations of the modified model and the unmodified model. The comparison showed that the surface fluxes and cloudiness in the modified model simulations were much more accurate. The planetary albedo in the model was also realistic. Weaknesses persisted in the models positioning of the Inter-tropical convergence zone (ICTZ) and in the temperature estimates for polar regions. A second simulation of the model following reparametrization of the cloud data showed improved results and these are described in detail.

Sud, Y. C.↗

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

Evolution of rotating interstellar clouds. II - The collapse of protostars of 1, 2, and 5 solar masses

Numerical calculations have been made for the early stages of collapse of axisymmetric rotating protostars of 1, 2, and 5 solar masses. The calculations employ a range of values of total angular momentum, as well as two types of initial density distribution. The effects of boundary conditions are tested by using constant volume and constant surface pressure with identical initial conditions. The principal result of the calculations is that, in all cases tried, the collapse leads to the formation of a ring structure in the interior of the cloud, with a local density minimum at the center of the cloud. The rings approach equilibrium with a structure consistent with that of previous analytic determinations, after which they undergo further gravitational collapse. The collapse of a two-solar-mass cloud, similar to that assumed by Cameron and Pine (1973), does not appear to lead to the equilibrium nebula these authors construct.

Black, D. C.↗

Numerical simulation of polar lows and comma clouds using simple dry models

Linear and nonlinear numerical channel models are used to simulate polar low/comma cloud evolution. The basic state of the model is idealized and can be specified analytically. It has strong horizontal as well as vertical wind shear and implicitly includes the effect of sensible heat fluxes from the lower boundary. This is done by having a layer of reduced stability present in the lower troposphere. The results of the linear model study are presented and used to provide input for the nonlinear model integration. It is shown that, given sufficient horizontal resolution, many features of polar low/comma clouds can be simulated by the nonlinear primitive equations model and the idealized basic state, in particular a rapidly growing disturbance with a wavelength on the order of 1000 km.

Mudrick, Stephen E.↗

Variation and evolution of atmospheric structure over the SEA BB season as seen from aircraft and reanalysis

The presence of absorbing aerosols and atmospheric water vapor will impact clouds both radiatively and dynamically. The atmosphere over the southeast Atlantic Ocean (SEA) experiences consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward into the free troposphere where it overlies and ultimately mixes into the underlying stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region over three deployments in September 2016, August 2017, and October 2018. Measurements included in situ profile measurements of aerosol physical and optical properties, trace gas concentrations, and cloud properties, as well as column measurements of aerosol optical depth and trace gas concentrations from an airborne sun photometer, allowing for calculation of radiative heating at different altitudes. Here we present results from the three ORACLES deployments over the southeast Atlantic Ocean. The airborne observations capture both seasonal patterns (August through October) and spatial patterns (north/south and east/west) in the vertical smoke distribution and its correlation to atmospheric specific humidity over the SEA basin. We describe the observed variations and show that the variability in both meteorological and emissions is largely captured in the European Centre for Medium-range Weather Forecasting Copernicus Atmosphere Monitoring Service (ECMWF CAMS) reanalysis, which allows for a more systematic examination of the relative frequency of observed conditions and their radiative impact over the region. Finally, we discuss the broader radiative and dynamical implications of these results for conditions of biomass burning aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗

Increased importance of aerosol–cloud interactions for surface PM 2.5 pollution relative to aerosol–radiation interactions in China with the anthropogenic emission reductions

Surface fine particulate matter (PM 2.5 ) pollution can be enhanced by feedback processes induced by aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). Many previous studies have reported enhanced PM 2.5 concentrations induced by ARIs and ACIs for episodic events in China. However, few studies have examined the changes in the ARI- and ACI-induced PM 2.5 enhancements over a long period, though the anthropogenic emissions have changed substantially in the last decade. In this study, we quantify the ARI- and ACI-induced PM 2.5 changes for 2013–2021 under different meteorology and emission scenarios using the Weather Research and Forecasting model with Chemistry (WRF-Chem), and we investigate the driving factors behind the changes. Our results show that, in January 2013, when China suffered from the worst PM 2.5 pollution, the PM 2.5 enhancement induced by ARIs in eastern China (5.59 µg m −3 ) was larger than that induced by ACIs (3.96 µg m −3 ). However, the ACI-induced PM 2.5 enhancement showed a significantly smaller decrease ratio (51 %) than the ARI-induced enhancement (75 %) for 2013–2021, making ACIs more important for enhancing PM 2.5 concentrations in January 2021. Our analyses suggest that the anthropogenic emission reductions played a key role in this shift. Owing to only anthropogenic emission reductions, the ACI-induced PM 2.5 enhancement decreased by 43 % in January, which was lower than the decrease ratio of the ARI-induced enhancement (57 %). The relative change in ARI- and ACI-induced PM 2.5 enhancement in July was similar to the pattern observed in January, caused by anthropogenic emission reductions. The primary reason for this phenomenon is that the decrease in ambient PM 2.5 for 2013–2021 caused a disproportionately small decrease in the liquid water path (LWP) and an increase in the cloud effective radius (Re) under the condition of high PM 2.5 concentrations. Therefore, the surface solar radiation attenuation (and, hence, the boundary layer height reduction) caused by ACIs decreased slower than that caused by ARIs. Moreover, the lower decrease ratio of the ACI-induced PM 2.5 enhancement was dominated by the lower decrease ratio of ACI-induced secondary PM 2.5 component enhancement, which was additionally caused by the smaller decrease ratio of the air temperature reduction and the relative humidity (RH) increase. Our findings indicate that, with the decrease in ambient PM 2.5 , the ACI-induced PM 2.5 enhancement inevitably becomes more important. This needs to be considered in the formulation of control policies to meet the national PM 2.5 air quality standard.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗