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Columnar Aerosol Types and Compositions Over Peninsular Southeast Asia Based on Long-Term AERONET Data

Aerosol chemical components such as black carbon (BC) and brown carbon (BrC) regulate aerosol optical properties, which in turn drive the atmospheric radiative forcing estimations due to aerosols. In this study, we used the long-term measurements from AERONET (Aerosol Robotic Network) to better understand the aerosol types and composition with respect to their seasonal and spatial variabilities in peninsular Southeast Asia (PSEA, here defined as Vietnam, Cambodia, Thailand, Laos, and Myanmar). Two methods (i.e., aerosol type cluster and aerosol component retrieval) were applied to determine the aerosol type and chemical composition during the biomass-burning (BB) season. AERONET sites in northern PSEA showed a higher AOD (aerosol optical depth) compared to that of southern PSEA. Differences in land use pattern, geographic location, and weather regime caused much of the aerosol variability over PSEA. Lower single-scattering albedo (SSA) and higher fine-mode fraction (FMF) values were observed in February and March, suggesting the predominance of BB type aerosols with finer and stronger absorbing particles during the dry season. However, we also found that the peak BB month (i.e., March) in northern PSEA may not coincide with the lowest SSA once dust particles have mixed with the other aerosols. Furthermore, we investigated two severe BB events in March of 2014 and 2015, revealing a significant BrC fraction during BB event days. On high AOD days, although the BC fraction was high, the BrC fraction remained low due to lack of aerosol aging. This study highlights the dominance of carbonaceous aerosols in the PSEA atmosphere during the BB season, while also revealing that transported dust particles and BrC aerosol aging may introduce uncertainties into the aerosol radiative forcing calculation.

Sheng-Hsiang Wang↗

The NASA Micro Pulse Lidar Network (MPLNET): Early Results from Development of Diurnal Climatologies

The NASA Micro Pulse Lidar Network (MPLNET) is a federated network of micro pulse lidar sites, mostly co-located with the NASA Aerosol Robotic Network (AERONET), providing information on the vertical properties of both aerosols and clouds. MPLNET began in 2000, and has grown to include ~80 sites worldwide. MPLNET data is collected continuously, offering the ability to examine diurnal changes in aerosol and cloud properties. To date, twelve sites have over 10 years of data and more will hit this milestone soon. Here we present early results from development of Level 3 monthly diurnal climatologies from MPLNET.

Ellsworth J Welton↗

Investigation of Overlap Correction Techniques for Application in the Micro-Pulse Lidar Network (MPLNET)

The Micro-Pulse Lidar NETwork (MPLNET) is comprised of micro-pulse lidars (MPL) stationed around the globe to provide measurements of aerosol and cloud vertical distribution on a continuous basis. MPLNET sites are co-located with sunphotometers in the AErosol Robotic NETwork (AERONET) to provide joint measurements of aerosol optical depth, size, and other inherent optical properties. The IPCC 2001 report discusses . the importance of obtaining routine measurements of aerosol vertical structure, especially for absorbing aerosols. MPLNET provides exactly this sort of measurement, including calculation of aerosol extinction profiles, in a near real-time basis for all sites in the network. In order to obtain aerosol profiles, near range signal returns (0-6 km) must be accurately measured by the MPL. This measurement is complicated by the instrument s overlap range: Le., the minimum distance at which returning signals are completely in the instrument s field-of-view (FOV). Typical MPL overlap distances are large, between 5 - 6 km, due to the narrow FOV of the MPL receiver. A function describing the MPL overlap must be determined and used to correct signals in this range. Currently, overlap functions for MPLNET are determined using horizontal MPL measurements along a path with 10-1 5 km clear line-of-sight and a homogenous atmosphere. These conditions limit the location and ease in which successful overlaps can be obtained. Furthermore, the current MPLNET process of correcting for overlap increases the uncertainty and bias error for the near range signals and the resulting aerosol extinction profiles. To address these issues, an alternative overlap correction method using a small-diameter, wide FOV receiver is being considered for potential use in MPLNET. The wide FOV receiver has a much shorter overlap distance and will be used to calculate the overlap function of the MPL receiver. This approach has a significant benefit in that overlap corrections could be obtained without the need for horizontal measurements. A review of both overlap methods is presented, including a discussion of the impact on reducing the uncertainty and bias error in MPLNET aerosol profiles.

Berkoff, Timothy A.↗

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD Retrievals Against Ground Sunphotometer Observations Over East Asia

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51% of VIIRS Environmental Data Record (EDR) AOD, 37% of GOCI AOD, 33% of VIIRS Intermediate Product (IP) AOD, 26% of Terra MODIS C6 3km AOD, and 16% of Aqua MODIS C6 3km AOD fell within the reference expected error (EE) envelope (+/-0.05/+/- 0.15 AOD). Comparing against AERONET AOD over the JapanSouth Korea region, 64% of EDR, 37% of IP, 61% of GOCI, 39% of Terra MODIS, and 56% of Aqua MODIS C6 3km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3km products had positive biases.

Xiao, Q.↗

A Network for Standardized Ocean Color Validation Measurements

The Aerosol Robotic Network (AERONET) was developed to support atmospheric studies at various scales with measurements from worldwide distributed autonomous sunphotometers [Holben et al. 1998]. AERONET has now extended its support to marine applications through the additional capability of measuring the radiance emerging from the sea with modified sun-photometers installed on offshore platforms like lighthouses, navigation aids, oceanographic and oil towers. The functionality of this added network component called AERONET - Ocean Color (AERONET-OC), has been verified at different sites and deployment structures over a four year testing phase. Continuous or occasional deployment platforms (see Fig. 1) included: the Acqua Alta Oceanographic Tower (AAOT) of the Italian National Research Council in the northern Adriatic Sea since spring 2002; the Martha s Vineyard Coastal Observatory (MVCO) tower of the Woods Hole Oceanographic Institution in the Atlantic off the Massachusetts coast for different periods since spring 2004; the TOTAL Abu-Al-Bukhoosh oil Platform (AABP, shown through an artistic rendition in Fig. 1) in the Persian (Arabian) Gulf in fall 2004; the Gustaf Dal n Lighthouse Tower (GDLT) of the Swedish Maritime Administration in the Baltic Sea in summer 2005; and the platform at the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) site located in the Atlantic Ocean off the Virginia coast since fall 2005. Data collected during the network testing phase, confirm the capability of AERONET-OC to support the validation of marine optical remote sensing products through standardized measurements of normalized water-leaving radiance, LWN, and aerosol optical thickness, a, at multiple coastal sites.

Zibordi, Giuseppe↗

Lidar-Radiometer Inversion Code (LIRIC) for the Retrieval of Vertical Aerosol Properties from Combined Lidar Radiometer Data: Development and Distribution in EARLINET

This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code)algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar radiometric input data we use measurements from European Aerosol Re-search Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data by the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height-dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Inter-comparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLNET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.

Chaikovsky, A.↗

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from τMI [basic algorithm] = 0.41τAERONET + 0.16 to τMI [new algorithm] = 0.70τAERONET + 0.01.

aerosols↗

Validation and Expected Error Estimation of Suomi-NNP VIIRS Aerosol Optical Thickness and Angstrom Exponent with AERONET

The new-generation polar-orbiting operational environmental sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite, provides critical daily global aerosol observations. As older satellite sensors age out, the VIIRS aerosol product will become the primary observational source for global assessments of aerosol emission and transport, aerosol meteorological and climatic effects, air quality monitoring, and public health. To prove their validity and to assess their maturity level, the VIIRS aerosol products were compared to the spatiotemporally matched Aerosol Robotic Network (AERONET)measurements. Over land, the VIIRS aerosol optical thickness (AOT) environmental data record (EDR) exhibits an overall global bias against AERONET of 0.0008 with root-mean-square error(RMSE) of the biases as 0.12. Over ocean, the mean bias of VIIRS AOT EDR is 0.02 with RMSE of the biases as 0.06.The mean bias of VIIRS Ocean Angstrom Exponent (AE) EDR is 0.12 with RMSE of the biases as 0.57. The matchups between each product and its AERONET counterpart allow estimates of expected error in each case. Increased uncertainty in the VIIRS AOT and AE products is linked to specific regions, seasons, surface characteristics, and aerosol types, suggesting opportunity for future modifications as understanding of algorithm assumptions improves. Based on the assessment, the VIIRS AOT EDR over land reached Validated maturity beginning 23 January 2013; the AOT EDR and AE EDR over ocean reached Validated maturity beginning 2 May 2012, excluding the processing error period 15 October to 27 November 2012. These findings demonstrate the integrity and usefulness of the VIIRS aerosol products that will transition from S-NPP to future polar-orbiting environmental satellites in the decades to come and become the standard global aerosol data set as the previous generations missions come to an end.

Huang, Jingfeng↗

Inversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals

NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in the time frame of late 2022 to early 2023, will carry the Ocean Color Instrument (OCI), a hyperspectral scanning radiometer, and two multiangle polarimeters (MAPs), the UMBC Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the SRON Spectro-Polarimeter for Planetary EXploration one (SPEXone). One purpose of the PACE MAPs is to better characterize aerosol properties, which can then be used to improve atmospheric correction for the retrieval of ocean color in coastal waters. Though this is theoretically promising, the use of MAP data in the atmospheric correction of colocated hyperspectral ocean color measurements have not yet been well demonstrated. In this work, we performed aerosol retrievals using the MAP measurements from the Research Scanning Polarimeter (RSP) and demonstrate its application to the atmospheric correction of hyperspectral radiometric measurements from SPEX airborne. Both measurements were collected on the same aircraft from the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign in 2017. Two cases over ocean with small aerosol loading (aerosol optical depth ∼0.04) are identified including colocated RSP and SPEX airborne measurements and Aerosol Robotic Network (AERONET) ground-based observations. The aerosol retrievals are performed and compared with two options: one uses reflectance measurement only and the other uses both reflectance and polarization. It is demonstrated that polarization information helps reduce the uncertainties of aerosol microphysical and optical properties. The retrieved aerosol properties are then used to compute the contribution of atmosphere and ocean surface for atmospheric correction over the discrete bands from RSP measurements and the hyperspectral SPEX airborne measurements. The water-leaving signals determined this way are compared with both AERONET and Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color products for performance analysis. The results and lessons learned from this work will provide a basis to fully exploit the information from the unique combination of sensors on PACE for aerosol characterization and ocean ecosystem research.

Meng Gao↗

Spatiotemporal Characteristics of the Association between AOD and PM over the California Central Valley

Many air pollution health effects studies rely on exposure estimates of particulate matter (PM) concentrations derived from remote sensing observations of aerosol optical depth (AOD). Simple but robust calibration models between AOD and PM are therefore important for generating reliable PM exposures. We conduct an in-depth examination of the spatial and temporal characteristics of the AOD-PM2.5 relationship by leveraging data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) field campaign where eight NASA Aerosol Robotic Network (AERONET) sites were co-located with EPA Air Quality System (AQS) monitoring sites in California’s Central Valley from November 2012 to April 2013. With this spatiotemporally rich data we found that linear calibration models (R(exp 2) = 0.35, RMSE = 10.38 µg/cu.m) were significantly improved when spatial (R(exp 2) = 0.45, RMSE = 9.54 µg/cu.m), temporal (R(exp 2) = 0.62, RMSE = 8.30 µg/cu.m), and spatiotemporal (R(exp 2) = 0.65, RMSE = 7.58 µg/cu.m) functions were included. As a use-case we applied the best spatiotemporal model to convert space-borne MultiAngle Imaging Spectroradiometer (MISR) AOD observations to predict PM2.5 over the region (R(exp 2) = 0.60, RMSE = 8.42 µg/cu.m). Our results imply that simple AERONET AOD-PM2.5 calibrations are robust and can be reliably applied to space-borne AOD observations, resulting in PM2.5 prediction surfaces for use in downstream applications.

Meytar Sorek-Hamer↗

Validation of MODIS Aerosol Optical Depth Retrieval Over Land

Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.

Chu, D. A.↗

Aerosol Properties over the Indo-Gangetic Plain: A Mesoscale Perspective from the TIGERZ Experiment

High aerosol loading over the northern Indian subcontinent can result in poor air quality leading to human health consequences and climate perturbations. The international 2008 TIGERZ experiment intensive operational period (IOP) was conducted in the Indo \Gangetic Plain (IGP) around the industrial city of Kanpur (26.51degN, 80.23deg E), India, during the premonsoon (April-June). Aerosol Robotic Network (AERONET) Sun photometers performed frequent measurements of aerosol properties at temporary sites distributed within an area covering 50 sq km around Kanpur to characterize pollution and dust in a region where complex aerosol mixtures and semi \bright surface effects complicate satellite retrieval algorithms. TIGERZ IOP Sun photometers quantified aerosol optical depth (AOD) increases up to 0.10 within and downwind of the city, with urban emissions accounting for 10 C20% of the IGP aerosol loading on deployment days. TIGERZ IOP area \averaged volume size distribution and single scattering albedo retrievals indicated spatially homogeneous, uniformly sized, spectrally absorbing pollution and dust particles. Aerosol absorption and size relationships were used to categorize black carbon and dust as dominant absorbers and to identify a third category in which both black carbon and dust dominate absorption.Moderate Resolution Imaging Spectroradiometer (MODIS) AOD retrievals with the lowest quality assurance (QA > or = 0) flags were biased high with respect to TIGERZ IOP area \averaged measurements. MODIS AOD retrievals with QA 0 had moderate correlation (R(sup 2) = 0.52-69) with the Kanpur AERONET site, whereas retrievals with QA > 0 were limited in number. Mesoscale \distributed Sun photometers quantified temporal and spatial variability of aerosol properties, and these results were used to validate satellite retrievals.

Giles, David M.↗

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

remote sensing↗

Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995-2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003-2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the validation procedure and cause us to caution against a direct extrapolation of the presented validation results to the entirety of the GACP dataset.

MODIS (radiometry)↗

Assimilation of AERONET and MODIS AOT Observations Using Variational and Ensemble Data Assimilation Methods and Its Impact on Aerosol Forecasting Skill

Data assimilation of Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting currently makes use of a deterministic NAAPS simulation coupled to Navy Variational Data Assimilation System for aerosol optical depth, a two-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow-dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the two-dimensional variational system can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT> 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24 h forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24 h forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating that AERONET could serve as a backup observation network for over-land synoptic-scale aerosol events.

Rubin, Juli I.↗

Evaluation of Aerosol Data Assimilation and Forecasts in the NASA GEOS Model during the ASIA-AQ Campaign

Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.

Seunghee Lee↗

An Overview of the Micro Pulse Lidar Network (MPLNET)

The NASA Micro Pulse Lidar Network (MPLNET) is a federated network of Micro Pulse Lidar (MPL) systems designed to measure aerosol and cloud vertical structure continuously, day and night, over long time periods required to contribute to climate change studies and provide ground validation for models and satellite sensors in the NASA Earth Observing System (FOS). At present, there are eighteen active sites worldwide, and several more in the planning stage. Numerous temporary sites are deployed in support of various field campaigns. Most MPLNET sites are co-located with sites in the NASA Aerosol Robotic Network (AERONET) to provide both column and vertically resolved aerosol and cloud data. MPLNET data and more information on the project are available at http://mpinet.gsfc.nasa.gov . Here we present a summary of the first ten years of MPLNET, along with an overview of our current status, specifically our version two data products and applications. Future network plans will be presented, with a focus on our activities in South East Asia.

Welton, Ellsworth↗