Goddard Chemistry Aerosol Radiation And Transport Research Articles

Evaluating the sensitivity of fine particulate matter (PM2.5) simulations to chemical mechanism in WRF-Chem over Delhi

Accurate prediction of PM2.5, its optical properties and dominant chemical components are essential for air quality studies. In this study, we investigated the effects of two gas phase chemical schemes coupled with three aerosol mechanisms on the simulated PM2.5 mass concentration in Delhi using the Weather Research and Forecasting model with Chemistry module (WRF-Chem). The model was employed to cover the entire northern region of India at 10 km horizontal spacing and results were compared with comprehensive field data set on dominant PM2.5 chemical compounds from the Winter Fog EXperiment (WiFEX) at the Indira-Gandhi International Airport, New Delhi, and surface PM2.5 observations in Delhi (17 sites), Punjab (3 sites), Haryana (4 sites), Uttar Pradesh (7 sites) and Rajasthan (17 sites). The Model for Ozone and related Chemical Tracers (MOZART) gas-phase chemical mechanism coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol scheme were selected in the first experiment as it is currently employed in the operational air quality forecasting system of Ministry of Earth Sciences (MoES), Government of India. Other two simulations were performed with the MOZART gas phase chemical mechanism coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOZART-MOSAIC), and Carbon Bond 5 (CB-05) gas mechanism coupled with the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model (CB05 - MADE/SORGAM) aerosol mechanisms. The evaluation demonstrated that chemical mechanisms affect the evolution of gas-phase precursors and aerosol processes which in turn affect the optical depth and overall performance of the model for PM2.5. All the three chemical schemes underestimate the observed concentrations of major aerosol composition and precursor gases over Delhi. Comparison with observations suggests that, the simulations using MOZART gas-phase chemical mechanism with MOSAIC aerosol scheme performed better in simulating aerosols over Delhi and its optical depth over the IGP.

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

Abstract. The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources, sinks, and chemistry of aerosols within the Goddard Earth Observing System (GEOS), recently underwent a major refactoring and update, including a revision of the emissions datasets and the addition of brown carbon. A 4-year benchmark simulation utilizing the new version of the model code, termed GOCART Second Generation (GOCART-2G) and coupled to the Goddard Earth Observing System (GEOS) model, was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over Northern Hemisphere boreal forests, requiring further investigation and tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations; however, discrepancies between the Aqua and Terra satellites indicate there is a diurnal component to biases in aerosol optical depth over southern Asia and northern Africa. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months. Over Europe, GOCART-2G is unable to match the summertime peak in aerosol optical depth, opposing the observed late fall and early spring peaks in surface mass concentration. A comparison of the vertical profile of attenuated backscatter to observations from CALIPSO indicates the GEOS model is capable of capturing the vertical profile of aerosol; however, the mid-troposphere plumes of dust in the North Atlantic and smoke in the southeastern Atlantic are perhaps too low in altitude. The results presented highlight priorities for future development with GOCART-2G, including improvements for dust, biomass burning aerosols, and anthropogenic aerosols.

JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP

AbstractA three‐dimensional ensemble‐variational global aerosol data assimilation system based on the Joint Effort for Data assimilation Integration (JEDI) was developed for the Global Ensemble Forecast System‐Aerosols (GEFS‐Aerosols) coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model at the National Centers for Environmental Prediction. Aerosol mass mixing ratios in GEFS‐Aerosols were selected as control or analysis variables and were adjusted by assimilating 550 nm Aerosol Optical Depth (AOD) retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard the Suomi National Polar‐orbiting Partnership (S‐NPP) satellite produced by the National Environmental Satellite, Data, and Information Service (NESDIS) at National Oceanic and Atmospheric Administration (NOAA). The original NOAA/NESDIS S‐NPP VIIRS Level 2.0 550 nm AOD retrievals were converted to JEDI Interface for Observation Data Access format. AOD forward operator and its tangent‐linear and adjoint models were implemented based on GOCART in JEDI Unified Forward Operator. A stochastically perturbed emission (SPE) approach was developed in the Common Community Physics Package‐based GEFS‐Aerosols to account for aerosol emission uncertainty. One‐month retrospective and three‐month near‐real‐time experiments consistently showed improved GEFS‐Aerosols analyses and forecasts from assimilating VIIRS 550 nm AOD retrievals against independent NASA Aqua and Terra Moderate Resolution Imaging Spectroradiometer AOD retrievals, Aerosol Robotic Network AOD, and independent AOD and aerosol analyses from NASA and European Centre for Medium‐Range Weather Forecasts. Through scaling and perturbing aerosol emissions, SPE enhanced ensemble error‐spread consistency and further improved AOD assimilation. The valid‐time‐shifting ensemble approach in a cost‐effective manner of populating background ensembles showed positive impacts on AOD assimilation.

Comprehensive Satellite Observations and a Numerical Study of a Wintertime Shallow Sea Smoke Event in the Yellow Sea

Abstract A winter storm triggered a significant sea smoke with the northwesterly wind to the Yellow Sea, China, on 7 January 2021. The ocean responses to this event lasted about 3 days. Satellite observations show that the sea surface temperature dropped from 5.7° to 4.7°C on the following day and then recovered to the previous level; the chlorophyll-a, a bio-growth indicator, increased from 3.6 to 3.9 mg m−3 due to cooling-induced coastal upwelling between 7 and 9 January. Two buoys measurements showed that the air temperature dropped to −13.3°C and high relative humidity with a maximum value of 89.0% above the sea surface, creating favorable conditions for sea smoke generation. A Regional Ocean Modeling System (ROMS) and Weather Research and Forecasting (WRF) Model coupled model with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) chemical module was implemented to reproduce this sea smoke phenomenon and analyze the air–sea interaction. The 20°C temperature difference between extreme cold air (−13.3°C) and the relatively warm stable sea surface (4.7°–5.7°C) enhanced the seawater evaporation. In addition, we suppose the concentration of sea salt, a kind of condensation nucleus, with a particle diameter of 0.5–1.5 μm above the sea surface increased quickly on 7 January. The boiling-water-like sea surface was imaged on a synthetic aperture image. We developed an image analysis method to describe the cell-shaped texture characteristics imaged by Synthetic Aperture Radar (SAR). We also found that the sea surface imprints of sea smoke are governed by the thermal, not the dynamical instability. Significance Statement On 7 January 2021, a significant sea smoke event happened in the Yellow Sea. The ocean response to the event lasted 3 days. First, on a synoptic scale, this study presents the comprehensive satellite observations of the sea surface temperature drop and chlorophyll-a increase associated with the sea smoke. Second, a coupled air–sea interaction model with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) chemical module was implemented to reproduce this sea smoke phenomenon and identify which condensation nucleus induced such heavy sea smoke. Third, we developed an image analysis method to analyze high-resolution synthetic aperture radar images and found that the sea surface imprints of sea smoke are governed by the thermal, not the dynamical instability.

Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module

Abstract. In this paper, we rectify inconsistencies that emerge in the Weather Research and Forecasting model with chemistry (WRF-Chem) v3.2 code when using the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module. These inconsistencies have been reported, and corrections have been implemented in WRF-Chem v4.1.3. Here, we use a WRF-Chem experimental setup configured over the Middle East (ME) to estimate the effects of these inconsistencies. Firstly, we show that the old version underestimates the PM2.5 diagnostic output by 7 % and overestimates PM10 by 5 % in comparison with the corrected one. Secondly, we demonstrate that submicron dust particles' contribution was incorrectly accounted for in the calculation of optical properties. Therefore, aerosol optical depth (AOD) in the old version was 25 %–30 % less than in the corrected one. Thirdly, we show that the gravitational settling procedure, in comparison with the corrected version, caused higher dust column loadings by 4 %–6 %, PM10 surface concentrations by 2 %–4 %, and mass of the gravitationally settled dust by 5 %–10 %. The cumulative effect of the found inconsistencies led to the significantly higher dust content in the atmosphere in comparison with the corrected WRF-Chem version. Our results explain why in many WRF-Chem simulations PM10 concentrations were exaggerated. We present the methodology for calculating diagnostics we used to estimate the impacts of introduced code modifications. We share the developed Merra2BC interpolator, which allows processing Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) output for constructing initial and boundary conditions for chemical species and aerosols.

Aerosol optical depth assimilation for a modal aerosol model: Implementation and application in AOD forecasts over East Asia

A new aerosol optical depth (AOD) data assimilation (DA) module was developed in Gridpoint Statistical Interpolation (GSI) 3-dimensional variational (3DVAR) system, named FastJ/CRTM-AOD DA module. And applied to the Modal Aerosol Dynamics Model for Europe with the Secondary Organic Aerosol Model (MADE/SORGAM) in the Weather Research and Forecasting/Chemistry model (WRF/Chem). The Fast-J optical module in WRF/Chem was used as the observation operator of AOD. The corresponding Jacobian code was modified from the one of CRTM-AOD in GSI. This way obviated the need for the Jacobian code's generation, which was complex and difficult for the highly nonlinear observation operator. During the studying period (January and April of 2014), compared to the ground AOD observations, AOD DA reduced about 20% fractional error (FE) with MADE/SORGAM. The original DA framework, which applied to the Goddard Chemistry Aerosol Radiation and Transport (GOCART) mechanism, performed slightly better than the new assimilation scheme for the low-value AOD situations (value < 0.4). However, compared to the original DA framework, the new DA scheme show a notable improvement for the high-value (0.4 < value ≤ 1.2) and extreme-high-value (value > 1.2) AOD situations. FE can be reduced by 48% and 64%, respectively. It indicates that the AOD DA impacts on AOD forecasts vary significant between different aerosol mechanisms. Moreover, FastJ/CRTM-AOD DA module can be easily and efficiently applied to the other aerosol schemes and the other optical modules, which is important to the development on AOD assimilation.

Investigation of the “dust reservoir effect” of the Tarim Basin using WRF-GOCART model

The Taklamakan and Gobi Deserts are two important dust source regions which are located in northwestern China where the topography is complicated. In this study, a historical severe dust episode was reconstructed and the subsequent dust behavior influenced by the topography was investigated by using the Weather Research and Forecasting (WRF) model coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. Based on the validated simulation results and model sensitivity trials, the study suggest that the topography of the Tarim Basin can function as a “dust reservoir,” which indicates that the basin can trap the ground-released dust at the beginning, and then re-release the trapped dust at a later time as a secondary source if the meteorological conditions permit. Moreover, to evaluate the “dust reservoir effect” of the Tarim Basin on the adjacent area, the mass concentration of PM10 was measured during the dust episode in a downwind city. Overall, given the dust modeling and PM10 sampling, the results indicate that the “dust reservoir” cannot only re-release dust aerosol as a secondary source, but also, the existence of a “dust reservoir” can prolong and exacerbate the impact on the air quality of the adjacent area.

Evaluation of dust extinction and vertical profiles simulated by WRF-Chem with CALIPSO and AERONET over North Africa

In this study, the Weather Research and Forecasting model with Chemistry (WRF-Chem) is applied to compare the simulated dust content and extinction coefficients from the Goddard Chemistry Aerosol Radiation and Transport (GOCART), the Air Force Weather Agency (AFWA) and University of Cologne (UoC) dust emission scheme available in WRF-Chem. The observations made by the AErosol RObotic NETwork (AERONET) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) are used to assess the model performance during the summer of 2006 over northern Africa. The results highlight that all the three schemes reproduce broadly the observed spatiotemporal distribution of dust content and extinction profile over northern Africa. However, differences exist in extent and intensity between the three emissions schemes and observations. All the three dust emission schemes reproduce the daily variation of the major dust events observed from the AERONET stations over northern Africa but failed to capture correctly the spatial distribution of the maximum zones of observed dust content by CALIOP. It is found that the simulated dust extinction profiles overestimate broadly the observation from CALIPSO in terms of vertical extent and magnitude over northern Africa. Our results reveal significant differences between the three schemes (GOCART, AFWA, and UoC). These differences between the schemes could be related to the calculation of the threshold wind speed in each scheme, which indicating the necessity to continue improving these dust emission schemes in the WRF-Chem model to better reduce uncertainties in the representation of dust plumes.

Sensitivity of simulating a dust storm over Central Asia to different dust schemes using the WRF-Chem model

Frequent dust storms have harm to human health and agricultural activities in Central Asia. However, there has been a great deal of uncertainty in prediction of dust storms in Central Asia. One of the important reasons is that the adaptability of different dust emission schemes has not been evaluated. Here, the Goddard Chemistry Aerosol Radiation and Transport (GOCART), Air Force Weather Agency (AFWA) and Shao2004 (Shao04) dust schemes coupled to the WRF-Chem model were used to simulate the severe dust storm occurred in Central Asia on 12–15 July 2016. Generally, this dust storm was initialed by a vortex at 500 hPa and surface cold front, and then swept across Turkmenistan, Uzbekistan and Tajikistan. The Shao04 case could represent the spatial-temporal evolution of the dust storm well, especially at the northern Iran and Turkmenistan, due to its better description of the physical process of dust emission. But it overestimated the aerosol optical depth (AOD) to the southeast of the Aral Sea, which might be associated with the uncertainties of the soil particle distribution dataset. The AFWA case simulated AOD as better as Shao04 case with improved soil moisture correction factors, saltation algorithms and particle size distributions although it had smaller particle size, indicating that smaller particles are assignable. The GOCART case showed the largest dust emission areas due to the low threshold velocity. Yet both the AFWA and GOCART scheme underestimated the high AOD over northern Iran owe to its low erodibility factors. The total dust emission of the four-day period in the Shao04 scheme was 11.9 Tg, which was 2–3 times larger than those obtained in the AFWA and GOCART schemes. The significant differences of dust emission between three dust schemes may essentially depend on the sensitivities of threshold friction velocity on surface property.

Influence of Wave State and Sea Spray on the Roughness Length: Feedback on Medicanes

Occasionally, storms that share many features with tropical cyclones, including the presence of a quasi-circular “eye” a warm core and strong winds, are observed in the Mediterranean. Generally, they are known as Medicanes, or tropical-like cyclones (TLC). Due to the intense wind forcings and the consequent development of high wind waves, a large number of sea spray droplets—both from bubble bursting and spume tearing processes—are likely to be produced at the sea surface. In order to take into account this process, we implemented an additional Sea Spray Source Function (SSSF) in WRF-Chem, model version 3.6.1, using the GOCART (Goddard Chemistry Aerosol Radiation and Transport) aerosol sectional module. Traditionally, air-sea momentum fluxes are computed through the classical Charnock relation that does not consider the wave-state and sea spray effects on the sea surface roughness explicitly. In order to take into account these forcing, we implemented a more recent parameterization of the sea surface aerodynamic roughness within the WRF surface layer model, which may be applicable to both moderate and high wind conditions. The implemented SSSF and sea surface roughness parameterization have been tested using an operative model sequence based on COAWST (Coupled Ocean Atmosphere Wave Sediment Transport) and WRF-Chem. The third-generation wave model SWAN (Simulating Waves Nearshore), two-way coupled with the WRF atmospheric model in the COAWST framework, provided wave field parameters. Numerical simulations have been integrated with the WRF-Chem chemistry package, with the aim of calculating the sea spray generated by the waves and to include its effect in the Charnock roughness parametrization together with the sea state effect. A single case study is performed, considering the Medicane that affected south-eastern Italy on 26 September 2006. Since this Medicane is one of the most deeply analysed in literature, its investigation can easily shed some light on the feedbacks between sea spray and drag coefficients.

Simulation of Severe Dust Events over Egypt Using Tuned Dust Schemes in Weather Research Forecast (WRF-Chem)

Weather Research and Forecasting model coupled with chemistry (WRF-Chem) was used to simulate selected severe dust storm events over Egypt in terms of the aerosol optical depth (AOD). Two severe events, which occurred on 22 January 2004 and 31 March 2013, are examined. The analysis includes three dust emission schemes: Goddard Chemistry Aerosol Radiation and Transport (GOCART), GOCART with Air Force Weather Agency (GOCART-AFWA), and GOCART with University of Cologne (GOCART-UOC). Each scheme was tested by adjusting coefficients related to the dust flux. The AOD and Single scattering albedo (SSA) from the model were compared against the same parameters derived from the Moderate-resolution Imaging Spectroradiometer (MODIS). The grid spacing for both of the data sets is 10 km. Results from the March 2013 event were also compared against point measurements from an Aerosol Robotic Network (AERONET) station in Cairo. Using WRF with built-in coefficients, all schemes resulted in underestimating AOD. After tuning the coefficients, it was possible to bring the model results closer to the observations from satellite and AERONET. Each severe event required a different tuning, depending on the origin and composition of the dust storm. Sensitivity analysis for each case is performed to identify the scheme that best simulates the given events based on spatial error distribution. A novel comparison of eigenvalue structures for images of both for AOD and SSA from model and MODIS was used. After tuning, the adjusted coefficient GOCART scheme is found to simulate AOD best across the country in both events. However, the results for the 2004 event from GOCART-UOC were closest to MODIS AOD over Cairo (within 5% bias). On the other hand, GOCART-AFWA produced nearest estimate of AOD for the 2013 event when compared to AERONET measurements (within 7% bias). For both of the events, SSA from GOCART and GOCART-AFWA schemes were found to be comparable to MODIS measurements with accuracy that was close to 98%. The accuracy from GOCART-UOC was around 93%.

Global and regional evaluation of a global model simulated AODs with AERONET and MODIS observations

ABSTRACTAerosol optical properties vary widely globally due to their short residence time and the large variability in their composition and size resulting from varying sources. In this study, we make use of the three‐dimensional global atmospheric chemistry transport model MOZART (Model for OZone And Related chemical Tracers), to simulate Aerosol Optical Depths (AODs) and compare with observations from MODIS (Moderate Resolution Imaging Spectroradiometer, level‐3) on board the Terra satellite and AERONET (AErosol RObotic NETwork level‐2), at regional and global scale for the period 2000–2007. The AOD values at a reference wavelength 550 nm are reported for all the data sets. Model and observations show intense aerosol burden over the parts of the world where developing countries are located. On a regional scale, varying features are noted for different regions depending upon topography, regional emissions and weather conditions. MOZART captures the general features observed in AERONET and MODIS fairly well; however, in biomass burning dominated regions (Central South America, South Africa, and North Australia) it underestimates the observed AOD. In industrial regions (North Europe and Mediterranean) MOZART overestimates the observations and over dust dominant regions (Saharan Africa, Middle East, and East Asia), the model AODs are comparable to AERONET and MODIS observations. In general, MOZART simulated AOD show similar seasonal and regional variability as observed in AERONET and MODIS. Our results are similar to the most commonly used models, i.e. GOCART (the GOddard Chemistry, Aerosol, Radiation, and Transport) and GEOS‐4 (Goddard Earth Observing System‐version 4).

Radiative effects of absorbing aerosols over northeastern India: Observations and model simulations

AbstractMultiyear measurements of spectral properties of aerosol absorption are examined over four geographically distinct locations of northeastern India. Results indicated significant spatiotemporal variation in aerosol absorption coefficients (σabs) with highest values in winter and lowest in monsoon. The western parts of the region, close to the outflow of Indo‐Gangetic Plains, showed higher values of σabs and black carbon (BC) concentration—mostly associated with fossil fuel combustion. But, the eastern parts showed higher contributions from biomass‐burning aerosols, as much as 20–25% to the total aerosol absorption, conspicuously during premonsoon season. This is attributed to a large number of burning activities over the Southeast Asian region, as depicted from Moderate Resolution Imaging Spectroradiometer fire count maps, whose spatial extent and magnitude peaks during March/April. The nearly consistent high values of aerosol index (AI) and layer height from Ozone Monitoring Instrument indicate the presence of absorbing aerosols in the upper atmosphere. The observed seasonality has been captured fairly well by Goddard Chemistry Aerosol Radiation and Transport (GOCART) as well as Weather Research and Forecasting–Chemistry (WRF‐Chem) model simulations. The ratio of column‐integrated optical depths due to particulate organic matter and BC from GOCART showed good coincidence with satellite‐based observations, indicating the increased vertical dispersion of absorbing aerosols, probably by the additional local convection due to higher fire radiative power caused by the intense biomass‐burning activities. In the WRF‐Chem though underperformed by different magnitude in winter, the values are closer or overestimated near the burnt areas. Atmospheric forcing due to BC was highest (~30 Wm−2) over the western part associated with the fossil fuel combustion.

Variability and predictability of West African monsoon on seasonal and decadal scales

Clim Dyn (2016) 47:3391–3392 DOI 10.1007/s00382-016-3429-4 EDITORIAL Variability and predictability of West African monsoon on seasonal and decadal scales Yongkang Xue 1 · Serge Janicot 2 · William K.‑M. Lau 3 Published online: 26 November 2016 © Springer-Verlag Berlin Heidelberg 2016 Recent observational evidence supports the notion that there are strong decadal climate variabilities in the Sahel and sur- rounding areas from the 1950s to the 2000s, not only in pre- cipitation, but also in sea surface temperature (SST), vegeta- tion cover, land use and land cover change (LULCC), and aerosol loading and spatial distributions (Xue et al. 2016; Boone et al. 2016; Gu et al. 2016). In the 2010 Climate Dynamics Special Issue “West African Monsoon and its Modeling,” the skills of general circulation models (GCMs) and regional climate models (RCMs) in properly simulating the West African monsoon (WAM) were extensively evalu- ated, and possible causes that contribute to model deficien- cies were investigated. While these studies provided basic understanding of the seasonal variations of WAM climatol- ogy, understanding of the complex interactions of WAM variability associated with SST, land surface, and aerosol forcings at different scales, particularly with respect to sea- sonal to decadal scale forcing, is still lacking. This special issue “Decadal variability of the West Afri- can monsoon, external surface forcings, and their mode- ling” aims to provide the latest research on the main WAM dynamic and physical processes, model predictability, and possible interactions between the WAM and external forc- ings at seasonal to decadal scales. The main themes of this * Yongkang Xue yxue@geog.ucla.edu Department of Geography, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA Laboratoire Atmospheres Milieux Observations Spatiales, Sorbonne-Universites, CNRS-UVSQ-UPMC, Paris, France Earth System Science Interdisciplinary Center, Joint Global Change Research Institute, University of Maryland, College Park, MD, USA special issue are: (1) intercomparison and evaluation of skills of GCMs and RCMs in simulating seasonal and dec- adal variability of WAM rainfall and relevant processes, and its association with SST, LULCC, and aerosol processes, as well as identification of major challenges, deficiencies, and uncertainties that remain in modeling WAM variabil- ity; (2) representations of major WAM characteristics and possible underlying physical and dynamic mechanisms; (3) application of observational and reanalyses data as a path- way for model physics evaluation and improvement, and in understanding the WAM variability; and (4) evaluation of RCM downscaling ability in terms of WAM decadal vari- ability. The papers in the special issue are mainly based on research conducted in conjunction with the second phase of the international West African Monsoon Modeling and Evaluation (WAMME II) project and the African Multidis- ciplinary Monsoon Analysis (AMMA) project. Most papers in this issue are from the WAMME II project focusing on the interactions between the WAM and external forcings. In the WAMME II experiment, realistic but ideal- ized forcings (setting to maximum forcing amplitude) are imposed to examine WAM responses in the WAMME II mod- els. Among them, Xue et al. (2016) investigate relative effects of the global and several major individual ocean basins on the WAM decadal variability and compare the SST’s role and the LULCC effect in initiating and modulating the decadal WAM variability and the 1980s Sahel drought. Boone et al. (2016) use recently available LULCC data to evaluate the sensitiv- ity of WAM seasonal variability to land surface processes and physical mechanisms involved. In addition to multi-model experiments, some of the individual models’ results are also presented. Using the aerosol data from the Goddard Chemis- try Aerosol Radiation and Transport (GOCART) model, Gu et al. (2016) compare aerosol effects over the WAM region and the Asian monsoon regions.

Natural and Anthropogenic Aerosol Trends from Satellite and Surface Observations and Model Simulations over the North Atlantic Ocean from 2002 to 2012

Abstract Aerosols contribute to Earth’s radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of the United States and the North Atlantic Ocean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation. MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (−0.030 decade−1). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM2.5 observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.

Climatology of the aerosol optical depth by components from the Multi-angle Imaging SpectroRadiometer (MISR) and chemistry transport models

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product has provided a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month over 16+ years since March 2000. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical – near or downwind of their major source regions. The statistical moments (means, standard deviations, and skewnesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from two chemistry transport models (CTMs), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) and SPectral RadIatioN-TrAnSport (SPRINTARS). Overall, the AOD distributions retrieved from MISR and modeled by GOCART and SPRINTARS agree with each other in a qualitative sense. Marginal distributions of AOD for each aerosol type in both MISR and models show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.

Comparison of aerosol optical properties above clouds between POLDER and AeroCom models over the South East Atlantic Ocean during the fire season

AbstractAerosol properties above clouds have been retrieved over the South East Atlantic Ocean during the fire season 2006 using satellite observations from POLDER (Polarization and Directionality of Earth Reflectances). From June to October, POLDER has observed a mean Above‐Cloud Aerosol Optical Thickness (ACAOT) of 0.28 and a mean Above‐Clouds Single Scattering Albedo (ACSSA) of 0.87 at 550 nm. These results have been used to evaluate the simulation of aerosols above clouds in five Aerosol Comparisons between Observations and Models (Goddard Chemistry Aerosol Radiation and Transport (GOCART), Hadley Centre Global Environmental Model 3 (HadGEM3), European Centre Hamburg Model 5‐Hamburg Aerosol Module 2 (ECHAM5‐HAM2), Oslo‐Chemical Transport Model 2 (OsloCTM2), and Spectral Radiation‐Transport Model for Aerosol Species (SPRINTARS)). Most models do not reproduce the observed large aerosol load episodes. The comparison highlights the importance of the injection height and the vertical transport parameterizations to simulate the large ACAOT observed by POLDER. Furthermore, POLDER ACSSA is best reproduced by models with a high imaginary part of black carbon refractive index, in accordance with recent recommendations.

Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States

We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations. Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure.

Global aerosol mixtures and their multiyear and seasonal characteristics

The optical and microphysical characteristics of distinct aerosol types in the atmosphere are not yet specified at the level of detail required for climate forcing studies. What is even less well known are the characteristics of mixtures of aerosol and, in particular, their precise global spatial distribution. Here, cluster analysis is applied to seven years of 3-hourly, gridded 2.5° × 2° aerosol optical depth data from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, one of the most-studied global simulations of aerosol type currently available, to construct a spatial partition of the globe into a finite number of aerosol mixtures. The optimal number of aerosol mixtures is obtained with a k-means algorithm with smart seeding in conjunction with a stopping condition based on applying the ‘law of diminishing returns’ to the norm of the Euclidean distance to provide upper and lower bounds on the number of clusters. Each cluster has a distinct composition in terms of the proportion of biomass burning, sulfate, dust and marine (sea salt) aerosol and this leads rather naturally to a taxonomy for labeling aerosol mixtures. In addition, the assignment of primary colors to constituent aerosol types enables true color-mixing and the production of easy-to-interpret maps of their distribution. The mean multiyear global partition as well as partitions deduced on the seasonal timescale are used to extract aerosol robotic network (AERONET) Level 2.0 Version 2 inversion products in each cluster for estimating the values of key optical and microphysical parameters to help characterize aerosol mixtures. On the multiyear timescale, the globe can be spatially partitioned into 10 distinct aerosol mixtures, with only marginally more variability on the seasonal timescale. In the context of the observational constraints and uncertainties associated with AERONET retrievals, bivariate analysis suggests that mixtures dominated by dust and marine aerosol can be detected with reference to their single scattering albedo and Angstrom exponent at visible wavelengths in conjunction with their fine mode fraction and sphericity. Existing multivariate approaches at classification appear to be more ambiguous. The approach presented here provides gridded (1° × 1°) mean compositions of aeorosol mixtures as well as tentative estimates of mean aerosol optical and microphysical parameters in planetary regions where AERONET sites do not yet exist. Spreadsheets of gridded cluster indices for multiyear and seasonal partitions are provided to facililate further study of the global distribution of aerosol mixtures and possibly for the selection of new AERONET site locations.

A GCM investigation of dust aerosol impact on the regional climate of North Africa and South/East Asia

The climatic effects of dust aerosols in North Africa and South/East Asia have been investigated using an atmospheric general circulation model, NCEP/GCM/SSiB (Simplified Simple Biosphere Model) and the three-dimensional aerosol data simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. GCM simulations show that due to the scattering and absorption of solar radiation by dust particles, surface temperature decreases over both regions, accompanied by a reduced sensible heat flux. However, precipitation responses are different in these two regions. Due to differences in dust location and the associated heating with respect to the rainfall band and circulation, the effect of dust could either enhance or suppress precipitation. Over the North Africa region where dust particles are mainly located to the north of rainfall band, heating of the air column by dust particles forces a stronger ascent motion over dust layers, which induces an anomalous subsidence (or a weakened upward motion) and suppressed cyclonic circulation to its south where precipitation reduces. Furthermore, both humidity and cloud decrease due to the heating in the middle troposphere (semi-direct effect). In South/East Asia, dust particles are located in the upper troposphere over the major rainfall band during the monsoon season, especially Southwest India and the coastal area of Bay of Bengal. Heating of the air column increases upward motion and strengthens cyclonic circulation. Humidity also increases due to the draw-in of the low level moist air. Therefore, cloud and precipitation increase over South/East Asia associated with dust effect. During the pre-monsoon season, when dust particles are located to the north of the monsoon rainfall band, the heating effect results in shifting precipitation northward. The heating of air column due to dust particles, not surface cooling, plays the major role in precipitation changes. The anomalous upward motion over dust regions will induce a subsidence to its south and subsequently reduce precipitation over that region. Therefore, the responses of circulation and precipitation to aerosol forcing depend on the relative location of dust aerosols with respect to rainfall band, which may explain the fact that contradictory results exist regarding whether the aerosol effect would enhance or suppress precipitation. The dust induced change in precipitation is actually more of redistribution rather than the simple action of increase or decrease.