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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Impacts of aerosols on seasonal precipitation and snowpack in California based on convection-permitting WRF-Chem simulations

Here, a version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42° N, 117–124° W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about –0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation, 3 % for SWE, and 7 % for surface runoff for the whole domain, while the corresponding numbers are 12, 10, and 10 % for the mountaintops. The reduction in SWE is more significant in a dry year, with 9 % for the whole domain and 16 % for the mountaintops. The maximum reduction of ~20 % in precipitation occurs in May and is associated with the maximum aerosol loading, leading to the largest decrease in SWE and surface runoff over that period. It is also found that dust aerosols can cause early snowmelt on the mountaintops and reduced surface runoff after April.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Comment on “A novel and facile decay path of Criegee intermediates by intramolecular insertion reactions via roaming transition states” [J. Chem. Phys. 142 , 124312 (2015)]

In a recent article, Nguyen et al. report the discovery of a new decomposition pathway for small Criegee intermediates. Prior to this publication, the lowest known pathway for decomposition of Criegee intermediates involved ring closure to form a dioxirane followed by ring opening to make a methylenebisoxy biradical, which can then isomerize or decompose via a variety of pathways. The new pathway reported by Nguyen et al. involves the partial cleavage of the OO bond of the Criegee intermediate forming nascent H 2 CO and O( 1 D) fragments. The O( 1 D) fragment then orbits around the H 2 CO fragment in a manner reminiscent of roaming radical reactions and eventually inserts into one of the CH bonds of the H 2 CO fragment leading directly to formic acid. The authors report saddle point geometries for this pathway determined at a number of different levels of theory in which the distance between the oxygen atom and the formaldehyde varies from 2.0 Å to 3.5 Å depending on the level of theory. Density functional theory (DFT) calculations are found to give more compact, planar saddle point structures while coupled cluster, CCSD(T), and complete active space self consistent field, CASSCF, optimizations lead to looser saddle point structures in which the O atom orbits above the plane of the H 2 CO fragment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

Assessment of Natural and Anthropogenic Aerosol Air Pollution In the Middle East Using MERRA-2, CAMS Data Assimilation Products, and High-Resolution WRF-Chem Model Simulations

Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA), and a high-resolution regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to evaluate natural and anthropogenic particulate matter (PM) air pollution in the Middle East (ME) during 2015–2016. Two Moderate Resolution Imaging Spectrometer (MODIS) retrievals – combined product Deep Blue and Deep Target (MODIS-DB&DT) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) – and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) observations as well as in situ PM measurements for 2016 were used for validation of the WRF-Chem output and both assimilation products. MERRA-2 and CAMS-OA assimilate AOD observations. WRF-Chem is a free-running model, but dust emission in WRF-Chem is tuned to fit AOD and aerosol volume size distributions obtained from AERONET. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical and aerosol species. SO2 emissions in WRF-Chem are based on the novel OMI-HTAP SO2 emission dataset. The correlation with the AERONET AOD is highest for MERRA-2 (0.72–0.91), MAIAC (0.63–0.96), and CAMSOA (0.65–0.87), followed by MODIS-DB&DT (0.56–0.84) and WRF-Chem (0.43–0.85). However, CAMS-OA has a relatively high positive mean bias with respect to AERONET AOD. The spatial distributions of seasonally averaged AODs from WRF-Chem, assimilation products, and MAIAC are well correlated with MODIS-DB&DT AOD product. MAIAC has the highest correlation (R = 0.8), followed by MERRA-2 (R = 0.66), CAMS-OA (R = 0.65), and WRF-Chem (R = 0.61). WRF-Chem, MERRA-2, and MAIAC underestimate and CAMS-OA overestimates MODIS-DB&DT AOD. The simulated and observed PM concentrations might differ by a factor of 2 because it is more challenging for the model and the assimilation products to reproduce PM concentration measured within the city. Although aerosol fields in WRF-Chem and assimilation products are entirely consistent, WRF-Chem is preferable for analysis of regional air quality over the ME due to its higher spatial resolution and better SO2 emissions. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. Mineral dust is the major contributor to PM (≈ 75%–95%) compared to other aerosol types. Near and downwind from the SO2 emission sources, non-dust aerosols (primarily sulfate) contribute up to 30% to PM(sub 2.5). The contribution of sea salt to PM in coastal regions can reach 5%. The contributions of organic matter, black carbon and organic carbon to PM over the Middle East are insignificant. In the major cities over the Arabian Peninsula, the 90th percentile of PM(sub 10) and PM(sub 2.5) (particles with diameters less than 10 and 2.5 μm, respectively) daily mean surface concentrations exceed the corresponding Kingdom of Saudi Arabia air quality limits. The contribution of the non-dust component to PM(sub 2.5) is < 25%, which limits the emission control effect on air quality. The mitigation of the dust effect on air quality requires the development of environment-based approaches like growing tree belts around the cities and enhancing in-city vegetation cover. The WRF-Chem configuration presented in this study could be a prototype of a future air quality forecast system that warns the population against air pollution hazards.

Alexander Ukhov↗
NASA NTRS2015

Development of a Grid-Independent Geos-Chem Chemical Transport Model (v9-02) as an Atmospheric Chemistry Module for Earth System Models

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been re-engineered to also serve as an atmospheric chemistry module for Earth system models (ESMs). This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of the GEOSChem scientific code, permitting the exact same GEOSChem code to be used as an ESM module or as a standalone CTM. In this manner, the continual stream of updates contributed by the CTM user community is automatically passed on to the ESM module, which remains state of science and referenced to the latest version of the standard GEOS-Chem CTM. A major step in this re-engineering was to make GEOS-Chem grid independent, i.e., capable of using any geophysical grid specified at run time. GEOS-Chem data sockets were also created for communication between modules and with external ESM code. The grid-independent, ESMF-compatible GEOS-Chem is now the standard version of the GEOS-Chem CTM. It has been implemented as an atmospheric chemistry module into the NASA GEOS- 5 ESM. The coupled GEOS-5-GEOS-Chem system was tested for scalability and performance with a tropospheric oxidant-aerosol simulation (120 coupled species, 66 transported tracers) using 48-240 cores and message-passing interface (MPI) distributed-memory parallelization. Numerical experiments demonstrate that the GEOS-Chem chemistry module scales efficiently for the number of cores tested, with no degradation as the number of cores increases. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemistry module means that the relative cost goes down with increasing number of cores in a massively parallel environment.

CTM↗
DOE OSTI2023

Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

radEq Add-On Module for CFD Solver Loci-CHEM

Loci-CHEM to be applied to flow velocities where surface radiation due to heating from compression and friction becomes significant. The module adds a radiation equilibrium boundary condition to the computational fluid dynamics (CFD) code to produce accurate results. The module expanded the upper limit for accurate CFD solutions of Loci-CHEM from Mach 4 to Mach 10 based on Space Shuttle Orbiter Re-Entry trajectories. Loci-CHEM already has a very promising architecture and performance, but absence of radiation equilibrium boundary condition limited the application of Loci-CHEM to below Mach 4. The immediate advantage of the add-on module is that it allows Loci-CHEM to work with supersonic flows up to Mach 10. This transformed Loci-CHEM from a rocket engine- heritage CFD code with general subsonic and low-supersonic applications, to an aeroheating code with hypersonic applications. The follow-on advantage of the module is that it is a building block for additional add-on modules that will solve for the heating generated at Mach numbers higher than 10.

McCloud, Peter↗
DOE OSTI2014

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

CAM5 physics suite↗
NASA NTRSDate not supplied

Ensemble Forecasting/Assimilation/Emissions Estimation with WRF-Chem/DART: Accomplishments, Lessons Learned, and Future Plans

Over the past ten years, we have been conducting research on regional ensemble atmospheric composition forecasting/data assimilation/emissions estimation with WRF-Chem/DART. WRF- Chem/DART integrates the Weather Research and Forecasting model (WRF) with online chemistry (WRF-Chem) into the Data Assimilation Research Testbed (DART). DART is an ensemble data assimilation system based on the ensemble adjustment Kalman filter (EAKF) with adaptive inflation, localization (physical and state space), and an optional non-Gaussian formulation of the EAKF. DART includes assimilation of meteorological and limited chemical observations. WRF-Chem/DART extends DART to include assimilation of: MOPITT CO; IASI CO and O3; MODIS AOD; OMI O3, NO2, and SO2; TROPOMI CO, O3, NO2, and SO2, TES CO, CO2 (research mode), O3, NH3, and CH4 (research mode); CrIS CO, O3, NH3, CH4 (research mode), and PAN; SCIAMACHY NO2; GOME2a NO2; MLS O3 and HNO3; and proxy TEMPO O3, and NO2 satellite retrievals as raw retrievals or as ‘compact phase space retrievals’ (CPSRs) for profile retrievals. WRF-Chem/DART also assimilates in situ atmospheric composition measurements and uses the ‘state augmentation method’ for emissions estimation. In our presentation, we will provide an overview of WRF-Chem/DART: • applications and results; • lessons learned from: (i) independent versus joint assimilation; (ii) total/partial column versus profile retrieval assimilation; (iii) joint in situ and retrieval assimilation; (iv) assimilation at grid resolutions ranging from 100 km to 4 km; (v) dynamic emissions estimation; and • future work related to wildfire emissions estimation and intercomparison of CMAQ (online)/JEDI and CMAQ (online and offline)/DART.

WRF-Chem/DART↗
DOE OSTI2014

Comparison of Mixed Layer Heights from Airborne High Spectral Resolution Lidar, Ground-based Measurements, and the WRP-Chem Model during CalNex and CARES

The California Research at the Nexus of Air Quality and Climate Change (CalNex) and Carbonaceous Aerosol and Radiative Effects Study (CARES) field campaigns during May and June 2010 provided a data set appropriate for studying characteristics of the planetary boundary layer (PBL). The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) was deployed to California onboard the NASA LaRC B-200 aircraft to aid incharacterizing aerosol properties during these two field campaigns. Measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 31 flights, many in coordination with other research aircraft and ground sites, constitute a diverse data set for use in characterizing the spatial and temporal distribution of aerosols, as well as the depth and variability of the daytime mixed layer (ML), which is a subset within the PBL. This work illustrates the temporal and spatial variability of the ML in the vicinity of Los Angeles and Sacramento, CA. ML heights derived from HSRL measurements are compared to PBL heights derived from radiosonde profiles, ML heights measured from ceilometers, and simulated PBL heights from the Weather Research and Forecasting Chemistry (WRF-Chem) community model. Comparisons between the HSRL ML heights and the radiosonde profiles in Sacramento result in a correlation coefficient value (R) of 0.93 (root7 mean-square (RMS) difference of 157 m and bias difference (HSRL radiosonde) of 5 m). HSRL ML heights compare well with those from the ceilometer in the LA Basin with an R of 0.89 (RMS difference of 108 m and bias difference (HSRL Ceilometer) of -9.7 m) for distances of up to 30 km between the B-200 flight track and the ceilometer site. Simulated PBL heights from WRF-Chem were compared with those obtained from all flights for each campaign, producing an R of 0.58 (RMS difference of 604 m and a bias difference (WRF-Chem HSRL) of -157 m) for CalNex and 0.59 (RMS difference of 689 m and a bias difference (WRF-Chem HSRL) of 220 m) for CARES. Aerosol backscatter simulations are also available from WRF15 Chem and are compared to those from HSRL to examine differences among the methods used to derive ML heights.

Scarino, Amy Jo↗
NASA NTRS2020

OMI Measurements of Bromine Monoxide and Implications for Missing Sources of Polar Bromine in GEOS-Chem

The OMI satellite instrument provides total column measurements of bromine monoxide (BrO) with daily global coverage. Reactive bromine compounds (Br and BrO) catalytically destroy ozone in both the stratosphere and troposphere. The current emission scheme of brominated source gases in the GEOS-Chem chemical transport model well represents the stratospheric burden of bromine. However, halogen research in GEOS-Chem has largely focused on the influence of halogens on the tropospheric oxidative capacity. In the troposphere, the distribution of brominated compounds is more variable and significant uncertainties remain in the chemical processes governing the sources and sinks of reactive bromine compounds. In this study, we use GEOS-Chem simulated stratospheric columns of BrO to separate the tropospheric signal of BrO from the OMI total column measurements. The resulting tropospheric BrO columns are used to identify seasonal and regional anomalies in tropospheric BrO not currently represented in GEOS-Chem. In particular, periods of elevated tropospheric BrO during polar spring are observable by OMI, and past studies have connected these so-called "bromine explosion" events to near complete removal of surface ozone. Due to significant uncertainties in the springtime polar source of reactive bromine, many global models, including GEOS-Chem, do not simulate these tropospheric ozone depletion events. Consequently, OMI-based tropospheric columns of BrO are useful tool for investigating the impact of bromine explosion events on tropospheric ozone depletion episodes as well as background air quality.

Wales, Pamela↗
DOE OSTI2021

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system

This study introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together with the assimilation of ''compact phase space retrievals'' of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination ($R^2$). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of compact phase space retrievals (CPSRs). CPSRs are obtained by preprocessing retrieval data sets with an algorithm that (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ~ 35 %, while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.

58 GEOSCIENCES↗
DOE OSTI2014

Regional Modeling of Dust Mass Balance and Radiative Forcing over East Asia using WRF-Chem

The Weather Research and Forecasting model with Chemistry (WRF-Chem) is used to investigate the seasonal and annual variations of mineral dust over East Asia during 2007-2011, with a focus on the dust mass balance and radiative forcing. A variety of measurements from in-stu and satellite observations have been used to evaluate simulation results. Generally, WRF-Chem reproduces not only the column variability but also the vertical profile and size distribution of mineral dust over and near the dust source regions of East Asia. We investigate the dust lifecycle and the factors that control the seasonal and spatial variations of dust mass balance and radiative forcing over the seven sub-regions of East Asia, i.e. source regions, the Tibetan Plateau, Northern China, Southern China, the ocean outflow region, and Korea-Japan regions. Results show that, over the source regions, transport and dry deposition are the two dominant sinks. Transport contributes to ~30% of the dust sink over the source regions. Dust results in a surface cooling of up to -14 and -10 W m-2, atmospheric warming of up to 20 and 15 W m-2, and TOA cooling of -5 and -8 W m-2 over the two major dust source regions of East Asia, respectively. Over the Tibetan Plateau, transport is the dominant source with a peak in summer. Over identified outflow regions, maximum dust mass loading in spring is contributed by the transport. Dry and wet depositions are the comparably dominant sinks, but wet deposition is larger than dry deposition over the Korea-Japan region, particularly in spring (70% versus 30%). The WRF-Chem simulations can generally capture the measured features of dust aerosols and its radaitve properties and dust mass balance over East Asia, which provides confidence for use in further investigation of dust impact on climate over East Asia.

balance↗