MODIS 3km Aerosol Product: Algorithm and Global Perspective

After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community

Estimating Marine Aerosol Particle Volume and Number from Maritime Aerosol Network Data

As well as spectral aerosol optical depth (AOD), aerosol composition and concentration (number, volume, or mass) are of interest for a variety of applications. However, remote sensing of these quantities is more difficult than for AOD, as it is more sensitive to assumptions relating to aerosol composition. This study uses spectral AOD measured on Maritime Aerosol Network (MAN) cruises, with the additional constraint of a microphysical model for unpolluted maritime aerosol based on analysis of Aerosol Robotic Network (AERONET) inversions, to estimate these quantities over open ocean. When the MAN data are subset to those likely to be comprised of maritime aerosol, number and volume concentrations obtained are physically reasonable. Attempts to estimate surface concentration from columnar abundance, however, are shown to be limited by uncertainties in vertical distribution. Columnar AOD at 550 nm and aerosol number for unpolluted maritime cases are also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) data, for both the present Collection 5.1 and forthcoming Collection 6. MODIS provides a best-fitting retrieval solution, as well as the average for several different solutions, with different aerosol microphysical models. The average solution MODIS dataset agrees more closely with MAN than the best solution dataset. Terra tends to retrieve lower aerosol number than MAN, and Aqua higher, linked with differences in the aerosol models commonly chosen. Collection 6 AOD is likely to agree more closely with MAN over open ocean than Collection 5.1. In situations where spectral AOD is measured accurately, and aerosol microphysical properties are reasonably well-constrained, estimates of aerosol number and volume using MAN or similar data would provide for a greater variety of potential comparisons with aerosol properties derived from satellite or chemistry transport model data

Commentary on using equivalent latitude in the upper troposphere and lower stratosphere

We discuss the use of potential vorticity (PV) based equivalent latitude (EqLat) and potential temperature (<i>θ</i>) coordinates in the upper troposphere and lower stratosphere (UTLS) for chemical transport studies. The main objective is to provide a cautionary note on using EqLat-<i>θ</i> coordinates for aggregating chemical tracers in the UTLS. Several examples are used to show 3-D distributions of EqLat together with chemical constituents for a range of <i>θ</i>. We show that the use of PV-<i>θ</i> coordinates may not be suitable for several reasons when tropospheric processes are an important part of a study. Due to the different static stability structures between the stratosphere and troposphere, the use of <i>θ</i> as a vertical coordinate does not provide equal representations of the UT and LS. Since the <i>θ</i> surfaces in the troposphere often intersect the surface of the Earth, the <i>θ</i> variable does not work well distinguishing the UT from the boundary layer when used globally as a vertical coordinate. We further discuss the duality of PV/EqLat as a tracer versus as a coordinate variable. Using an example, we show that while PV/EqLat serves well as a transport tracer in the UTLS region, it may conceal the chemical structure associated with wave breaking when used as a coordinate to average chemical tracers. Overall, when choosing these coordinates, considerations need to be made not only based on the time scale of PV being a conservative tracer, but also the specific research questions to be addressed

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution

Active and Passive Radiative Transfer Modeling of the Olympic Mountains Experiment

Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry Gas absorptiono Line-by-line calculationso Fast transmittance tables Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations Requires full Stokes matriceso And absorption vector Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon) Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs Atmospheric Informationo Temperatureo Pressure / heighto Water vapor Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference Corresponds to the presence of aligned icecrystals Look at trends for both simulations andobservations Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input Single frequency radar retrievals Multiple scattering enhancementapparent at W band Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015 DC-8 and ER-2 flightso Focus on APR-3 (DC-8) Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults Retrievals match probeso Good qualitative match Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction Significant amounts ofsupercooled liquid wate

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) datahas shown that major aerosol pollution events with very highfine mode AOD (>1.0 in midvisible) in theChina/Korea/Japan region are often observed to be associated with significant cloud cover. This makesremote sensing of these events difficult even for high temporal resolution Sun photometer measurements.Possible physical mechanisms for these events that have high AOD include a combination of aerosolhumidification, cloud processing, and meteorological covariation with atmospheric stability andconvergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloudscreening algorithms now allow for unprecedented ability to monitor these extremefine mode pollutionevents. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening)provides an even more comprehensive assessment offine mode AOD than L2 in current and previous dataversions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA dailyaveragefine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remotesensing of AOD often did not retrieve and/or identify some of the highestfine mode AOD events in thisregion. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDAfinemode AOD was significantly higher in magnitude, particularly for the highest AOD events that were oftenassociated with significant cloudiness

Commentary on using equivalent latitude in the upper troposphere and lower stratosphere

We discuss the use of potential vorticity (PV) based equivalent latitude (EqLat) and potential temperature (<i>θ</i>) coordinates in the upper troposphere and lower stratosphere (UTLS) for chemical transport studies. The main objective is to provide a cautionary note on using EqLat-<i>θ</i> coordinates for aggregating chemical tracers in the UTLS. Several examples are used to show 3-D distributions of EqLat together with chemical constituents for a range of <i>θ</i>. We show that the use of PV-<i>θ</i> coordinates may not be suitable for several reasons when tropospheric processes are an important part of a study. Due to the different static stability structures between the stratosphere and troposphere, the use of <i>θ</i> as a vertical coordinate does not provide equal representations of the UT and LS. Since the <i>θ</i> surfaces in the troposphere often intersect the surface of the Earth, the <i>θ</i> variable does not work well distinguishing the UT from the boundary layer when used globally as a vertical coordinate. We further discuss the duality of PV/EqLat as a tracer versus as a coordinate variable. Using an example, we show that while PV/EqLat serves well as a transport tracer in the UTLS region, it may conceal the chemical structure associated with wave breaking when used as a coordinate to average chemical tracers. Overall, when choosing these coordinates, considerations need to be made not only based on the time scale of PV being a conservative tracer, but also the specific research questions to be addressed

A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR

The Collection 6 MODIS aerosol products over land and ocean

The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution