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Variable Lidar Ratios for Marine and Dusty Marine Using MODIS AOD Constrained Retrievals and GOCART Model Simulations and their Impact on Level 2 CALIPSO Data Products in Version 5

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO provided global measurements of attenuated backscatter profiles of various tropospheric aerosol species from June 2006 through June 2023. Extinction profiles are retrieved from these backscatter measurements by assuming a value for the extinction-to-backscatter or lidar ratio (LR). Up until version V4.51 of the data products, only a constant global value for each of the species has been used, spatially and temporally. However, it has been well known from various ground-based measurements that LRs of each aerosol species can potentially vary spatially as well seasonally. For the forthcoming Version 5 of the CALIPSO products, the CALIPSO team will implement variable lidar ratios at 532 nm for the species classified as “marine” and “dusty marine”. Here we present the essential elements of this scheme, which involves estimating lidar ratios by constraining Fernald solutions for the CALIOP particulate backscatter profiles using aerosol optical depths (AOD) from collocated MODIS retrievals. To account for the lack of measurements in various regions and seasons (e.g., Arctic winters), we leverage collocated model sea-salt volume fractions (SSVF) simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and use an empirical relationship between the SSVF and LR to build hybrid climatological maps for the entire globe, i.e., using the modelled values when reliable values of the constrained LRs are not available. Initial evaluation of the resulting extinction profiles and corresponding AODs, both globally and in specific regions are presented using a limited amount of data. The primary improvement in AOD occurs in the coastal areas, like the Arabian Sea and Bay of Bengal. The estimated marine LR values in these regions are significantly higher than the constant value of 23 sr used in previous data releases, likely due to mixing with offshore pollution which results in higher AODs. Initial validation results using the CALIPSO Ocean Derived Column Optical Depth (ODCOD) retrievals and ground-based AERONET AOD measurements are presented.

CALIPSO↗

Mars' Water Vapor Mapping by the SPICAM IR Spectrometer: Five Martian Years of Observations

The SPICAM IR instrument on the Mars Express mission continuously observes the water vapor in the martian atmosphere starting from 2004 in the 1.38-micrometer spectral band. The water vapor column abundance is retrieved from nadir observations to characterize its spatial, seasonal and interannual variations. A reference set of SPICAM water vapor column abundances (zonally averaged) covering the time period from 2004 to 2013 (martian years 27-31) is available for a grid of 2 deg Ls 2 latitude, along with an average reference map of water vapor abundance combining all the martian years of Mars Express observations. Compared to the previous data retrieval by Fedorova et al. (Fedorova, A., Korablev, O., Bertaux, J.L., Rodin, A., Kiselev, A., Perrier, S. [2006]. J. Geophys. Res. 111, E09S08) the new processing algorithm includes many improvements concerning the calibration and assumed parameters. A major improvement is the account for aerosol scattering based on dust and water ice cloud optical depths measured by THEMIS/Mars Odyssey (Smith, M.D. [2009]. Icarus 202, 444-452). The account for multiple scattering by aerosol particles increases the retrieved water vapor amount by approximately 10% in polar areas during summer, and up to 60-70% for large solar zenith angles. The sensitivity of the results to aerosol properties, surface albedo, solar spectrum, and water vapor vertical distribution has also been studied. The retrieved water vapor reveals nominal annual cycle with maximum abundance of about 60-70 pr. lm for the Northern summer and approximately 20 pr. lm for the Southern summer. The annual average amount of water has been estimated to be of 10-20 pr. micrometers, in agreement with other measurements. From year to year the seasonal cycle of water vapor abundance is very stable. An observed decrease during the MY 28 global dust storm cannot be fully attributed to the masking effect of dust, and indicates a real decrease of water amount near or above the surface. No evidence of diurnal variation of column water vapor amount was found, even though the 1.38-micrometer measurements are sensitive to the few lowermost kilometers above the surface.

Mars water vapor↗

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗

Tracking aerosols and SO2 clouds from the Raikoke eruption: 3D view from satellite observations

The 21 June 2019 eruption of the Raikoke volcano (Kuril Islands, Russia; 48° N, 153° E) produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. The dispersed SO2 and sulfate aerosols in the stratosphere were still detectable by multiple satellite sensors for many months after the eruption. For this study of SO2 and aerosol clouds we use data obtained from two of the Ozone Mapping and Profiler Suite sensors on the Suomi National Polar-orbiting Partnership satellite: total column SO2 from the Nadir Mapper and aerosol extinction profiles from the Limb Profiler as well as other satellite data sets. We evaluated the limb viewing geometry effect (the “arch effect”) in the retrieval of the LP standard aerosol extinction product at 674 nm. It was shown that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of stratospheric aerosol optical depth recorded at a wavelength of 674 nm lags the initial peak of SO2 mass by 1.5 months. Using satellite observations and a trajectory model, we examined the dynamics of an unusual atmospheric feature that was observed, a stratospheric coherent circular cloud of SO2 and aerosol from 18 July to 22 September 2019.

Eruption of the Raikoke volcano↗

Assessment of OMI Near-UV Aerosol Optical Depth over Land

This is the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the near-UV observations by the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. The OMI-retrieved AOD by the ultraviolet (UV) aerosol algorithm (OMAERUV version 1.4.2) was evaluated using collocated Aerosol Robotic Network (AERONET) level 2.0 direct Sun AOD measurements over 8 years (2005-2012). A time series analysis of collocated satellite and ground-based AOD observations over 8 years shows no discernible drift in OMI's calibration. A rigorous validation analysis over 4 years (2005-2008) was carried out at 44 globally distributed AERONET land sites. The chosen locations are representative of major aerosol types such as smoke from biomass burning or wildfires, desert mineral dust, and urban/industrial pollutants. Correlation coefficient (p) values of 0.75 or better were obtained at 50 percent of the sites with about 33 percent of the sites in the analysis reporting regression line slope values larger than 0.70 but always less than unity. The combined AERONET-OMAERUV analysis of the 44 sites yielded a p of 0.81, slope of 0.79, Y intercept of 0.10, and 65 percent OMAERUV AOD falling within the expected uncertainty range (largest of 30 percent or 0.1) at 440 nanometers. The most accurate OMAERUV retrievals are reported over northern Africa locations where the predominant aerosol type is desert dust and cloud presence is less frequent. Reliable retrievals were documented at many sites characterized by urban-type aerosols with low to moderate AOD values, concentrated in the boundary layer. These results confirm that the near-ultraviolet observations are sensitive to the entire aerosol column. A simultaneous comparison of OMAERUV, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue, and Multiangle Imaging Spectroradiometer (MISR) AOD retrievals to AERONET measurements was also carried out to evaluate the OMAERUV accuracy in relation to those of the standard aerosol satellite products. The outcome of the comparison indicates that OMAERUV, MODIS Deep Blue, and MISR retrieval accuracies in arid and semiarid environments are statistically comparable.

aerosol optical depth↗

MODIS Collection 6 MAIAC Algorithm

This paper describes the latest version of the algorithm MAIAC (Multi-Angle Implementation of Atmospheric Correction) used for processing the MODIS (Moderate-resolution Imaging Spectroradiometer) Collection6 data record. Since initial publication in 2011-2012, MAIAC has changed considerably to adapt to global processing and improve cloud/snow detection, aerosol retrievals and atmospheric correction of MODIS data. The main changes include (1) transition from a 25 to 1 km scale for retrieval of the spectral regression coefficient (SRC) which helped to remove occasional blockiness at 25 km scale in the aerosol optical depth (AOD) and in the surface reflectance, (2) continuous improvements of cloud detection, (3) introduction of smoke and dust tests to discriminate absorbing fine- and coarse mode aerosols, (4) adding over-water processing, (5) general optimization of the LUT (LookUp-Table)-based radiative transfer for the global processing, and others. MAIAC provides an interdisciplinary suite of atmospheric and land products, including cloud mask (CM), column water vapor (CWV), AOD at 0.47 and 0.55 m, aerosol type (background, smoke or dust) and fine-mode fraction over water; spectral bidirectional reflectance factors (BRF), parameters of Ross-thick Lisparse (RTLS) bidirectional reflectance distribution function (BRDF) model and instantaneous albedo. For snow-covered surfaces, we provide subpixel snow fraction and snow grain size. All products come in standard HDF4 (software library) format at 1 km resolution, except for BRF, which is also provided at 500 m resolution on a sinusoidal grid adopted by the MODIS Land team. All products are provided on per-observation basis in daily files except for the BRDF/Albedo product, which is reported every 8 days. Because MAIAC uses a time series approach, BRDF/Albedo is naturally gap-filled over land where missing values are filled-in with results from the previous retrieval. While the BRDF model is reported for MODIS Land bands 1-7 and ocean band 8, BRF is reported for both land and ocean bands 1-12. This paper focuses on MAIAC cloud detection, aerosol retrievals and atmospheric correction and describes MCD19 data products and quality assurance (QA) flags.

MAIAC Algorithm↗

Data associated with the manuscript “Radiative impact of record-breaking wildfires from integrated ground-based data” collected in Richland, Washington in September 2020

This data package is associated with the publication “Radiative impact of record-breaking wildfires from integrated ground-based data” submitted to Nature Scientific Reports (Kassianov et al., 2024). Data from ground-based measurements of shortwave and spectrally resolved irradiance and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges were assessed to quantify the radiative impact of the September 2020 wildfires that occurred in the Western United States. Data were collected in September 2020 by several ground-based instruments at the Atmospheric Measurements Laboratory (AML) located in Richland, Washington (46.3451, -119.2792). These data include (1) Aerosol Optical Depth (AOD); (2) spectrally resolved and shortwave (SW) irradiances; (3) backscatter profiles; (4) total sky images; and (5) near-surface ambient air temperatures.The data package consists of five sub-directories: (1) “AML_Ceilometer_”; (2)” AML_CSPHOT_”; (3) “AML_MFRSR_irradiances_”; (4) “AML_SW_irradiances_and_Temp_”; (5) “AML_TSI_images_”; and 6 files stored at the directory level, including the readme, file-level metadata file, and data dictionary. The file-level metadata file (the file ending in “_flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (the file ending in “_dd.csv”) describes each tabular column header’s unit, definition, and structure. Below are descriptions of each sub-directory:“AML_Ceilometer_” includes ceilometer data collected at the AML. These files contain the corresponding narratives of data. Details related to the ceilometer data can be found in Morris (2016). “AML_CSPHOT_” includes ascii files with high-temporal resolution (about 10-15 min) AML CSPHOT data and their daily-averaged counterparts. These two files contain the corresponding narratives of data. Details related to the CSPHOT data can be found in Gregory (2011). “AML_MFRSR_irradiances_” includes ascii files with the AML MFRSR-measured diffuse, normal, and total spectrally resolved irradiance. Details related to the MFRSR data can be found in Hodges and Michalsky (2016) and Koontz et al. (2013). “AML_SW_irradiances_+_Temp_” includes near-surface ambient air temperature and SW irradiances, namely direct normal, diffuse hemispherical, and total hemispheric (global), measured at the AML. These files also incorporate the corresponding narratives of data. Details related to the SW irradiances can be found in Andreas et al. (2018). “AML_TSI_images_” includes Total Sky Images (TSIs) collected at the AML. Details related to the TSI data can be found in Morris (2005).

54 ENVIRONMENTAL SCIENCES↗

The NASA Micro Pulse Lidar Network (MPLNET): Introduction of the New Version 3 Release

The NASA Micro-Pulse Lidar Network (MPLNET) is a global federated network of polarized Micro-Pulse Lidar (MPL) systems running continuously. MPLNET began in 2000, and there have been over 70 sites deployed worldwide, with 24 sites currently active and a few more planned over the next year. Seven of the long-term sites have 10+ years of data, and many more have 5+ years. Most sites are co-located with AERONET providing joint data on column and vertically resolved aerosol and cloud information. This presentation will introduce our new Version 3 MPLNET data. All sites in the network now feature eye-safe polarized backscatter MPL instruments, providing information on attenuated backscatter and particle shape. In addition to change with our signal data, we have an enhanced cloud product suite, a new PBL height product, and inclusion of the new AERONET lunar aerosol optical depth into MPLNET aerosol retrievals. A new quality flag process will be used to better describe all data products. Finally, a new data portal will provide near-real-time (NRT) access to all data products, including new quality assured NRT L1.5 products. Custom products developed for model specific applications will also be provided.

Welton, Ellsworth J.↗

Modeling and Evaluation of the Global Sea-Salt Aerosol Distribution: Sensitivity to Emission Schemes and Resolution Effects at Coastal/Orographic Sites

One of the major sources of uncertainty in model estimates of the global sea-salt aerosol distribution is the emission parameterization. We evaluate a new sea-salt aerosol life cycle module coupled to the online multi-scale chemical transport model NMMB/BSC-CTM. We compare 5 year global simulations using five state-of-the-art sea-salt open-ocean emission schemes with monthly averaged coarse aerosol optical depth (AOD) from selected AERONET sun photometers, surface concentration measurements from the University of Miami's Ocean Aerosol Network, and measurements from two NOAA/PMEL cruises (AEROINDOEX and ACE1). Model results are highly sensitive to the introduction of sea-surface-temperature (SST)-dependent emissions and to the accounting of spume particles production. Emission ranges from 3888 teragrams per year to 8114 teragrams per year, lifetime varies between 7.3 hours and 11.3 hours, and the average column mass load is between 5.0 teragrams and 7.2 teragrams. Coarse AOD is reproduced with an overall correlation of around 0.5 and with normalized biases ranging from +8.8 percent to +38.8 percent. Surface concentration is simulated with normalized biases ranging from minus 9.5 percent to plus 28 percent and the overall correlation is around 0.5. Our results indicate that SST-dependent emission schemes improve the overall model performance in reproducing surface concentrations. On the other hand, they lead to an overestimation of the coarse AOD at tropical latitudes, although it may be affected by uncertainties in the comparison due to the use of all-sky model AOD, the treatment of water uptake, deposition and optical properties in the model and/or an inaccurate size distribution at emission.

Bias↗

Comparison of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Earth Observing One (EO-1) Advanced Land Imager

We compare images from the Enhanced Thematic Mapper Plus (ETM+) sensor on Landsat-7 and the Advanced Land Imager (ALI) instrument on Earth Observing One (EO-1) over a test site in Rochester, New York. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, and grass fields, to urban areas. Nearly coincident cloud-free images were collected one minute apart on 25 August 2001. We also compare images of a forest site near Howland, Maine, that were collected on 7 September, 2001. We atmospherically corrected each pair of images with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmosphere model, using aerosol optical thickness and water vapor column density measured by in situ Cimel sun photometers within the Aerosol Robotic Network (AERONET), along with ozone density derived from the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. We present true-color composites from each instrument that show excellent qualitative agreement between the multispectral sensors, along with grey-scale images that demonstrate a significantly improved ALI panchromatic band. We quantitatively compare ALI and ETM+ reflectance spectra of a grassy field in Rochester and find < or equal to 6% differences in the visible/near infrared and approx. 2% differences in the short wave infrared. Spectral comparisons of forest sites in Rochester and Howland yield similar percentage agreement except for band 1, which has very low reflectance. Principal component analyses and comparison of normalized difference vegetation index histograms for each sensor indicate that the ALI is able to reproduce the information content in the ETM+ but with superior signal-to-noise performance due to its increased 12-bit quantization.

Pedelty, Jeffrey A.↗

Science Objectives of EOS-Aura's Ozone Monitoring Instrument (OMI)

OMI is a UV/VIS nadir solar backscatter spectrograph, which provides near global coverage in one day with a spatial resolution of 13 x 24 sq km. OMI is a new instrument, with a heritage from the European satellite instruments GOME, GOMOS and SCIAMACHY. OMI's unique capabilities for measuring important trace gases with a small footprint and daily global coverage, in conjunction with the other Aura instruments, will make a major contribution to our understanding of stratospheric and tropospheric chemistry and climate change. OMI will measure solar irradiance and Earth radiances in the wavelength range of 270 to 500 nm with spectral resolution of about 0.5 nm and a spectral sampling of about 2-3 per FWHM. From these observations, total columns of O3, NO2, BrO and SO2 will be derived from the back-scattered solar radiance using differential absorption spectroscopy (DOAS). The TOMS total ozone record will also be continued by employing the well established TOMS algorithm. Because of the high accuracy and spatial resolution of the measurements, a good estimate of tropospheric amounts of ozone and NO2 are expected. Ozone profiles will be derived using the optimal estimation method. The spectral aerosol optical depth will be determined from measurements between 340 and 500 nm. This will provide information on aerosol concentration, aerosol size distribution and aerosol type. This wavelength range makes it possible to retrieve aerosol information over both land and sea. OMI observations will also allow retrievals of cloud coverage and cloud heights. From these products, the UV-B flux at the surface can then be derived with high spatial resolution.

Levelt, P. F.↗

Airborne Sunphotometer Measurements of Aerosol Optical Depth and Water Vapor in ACE-Asia and Their Comparisons to Correlative Measurements

In the Spring 2001 phase of the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia), the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated on 15 of the 19 research flights of the NCAR C-130, while its 14-channel counterpart (AATS-14) flew successfully on all 19 research flights of the CIRPAS Twin Otter. ACE-Asia studied aerosol outflow from the Asian continent to the Pacific basin. It was designed to integrate suborbital and satellite measurements and models to reduce the uncertainty in calculations of the climate forcing due to aerosols. AATS-6 and AATS-14 measured solar beam transmission at six and 14 wavelengths (380-1021 and 354-1558 nm, respectively), yielding aerosol optical depth (AOD) spectra and columnar water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction spectra and water vapor concentration. In this paper, we plan to present examples of the following, preliminary findings that are based in part on our airborne sunphotometer measurements: (1) The wavelength dependence of sunphotometer-derived AOD and extinction indicates that supermicron dust was often a major component of the aerosol, frequently extending to high altitudes. The percentage of full-column AOD (525 nm) that Jay above 3 km was typically 34+/-13%. In contrast, the analogous percentage of columnar water vapor was only 10+/-4%; (2) Initial comparison studies between AOD data obtained by AATS-6 and AATS-14 during coordinated low-level flight legs show agreement well within the instruments' error bars; (3) Aerosol extinction has been derived from airborne in situ measurements of scattering (nephelometers) and absorption (particle soot/ absorption photometer, PSAP) or calculated from particle size distribution measurements (mobility analyzers and aerodynamic particle sizers). Comparison with corresponding extinction values derived from the Ames airborne sunphotometer measurements shows good agreement for the vertical distribution of aerosol layers. However, the level of agreement in absolute magnitude of the derived aerosol extinction/optical depth varied among the aerosol layers sampled; (4) Initial comparisons of sunphotometer and satellite-derived AOD using SeaWiFS, MISR and AVHRR show promising results. We also plan to include comparisons with MODIS and TOMS: (5) Initial comparisons of sunphotometer-derived AOD and aerosol extinction profiles with lidars in Tokyo and on a ship show reasonable agreement.

Schmid, B.↗

Upgrade of the NASA 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) to its Full Science Capability of Sun-Sky-Cloud-Trace Gas Spectrometry in Airborne Science Deployments

The objectives of this task in the AITT (Airborne Instrument Technology Transition) Program are to (1) upgrade the NASA 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument to its full science capability of measuring (a) direct-beam sun transmission to derive aerosol optical depth spectra, (b) sky radiance vs scattering angle to retrieve aerosol absorption and type (via complex refractive index spectra, shape, and mode-resolved size distribution), (c) zenith radiance for cloud properties, and (d) hyperspectral signals for trace gas retrievals, and (2) demonstrate its suitability for deployment in challenging NASA airborne multiinstrument campaigns. 4STAR combines airborne sun tracking, sky scanning, and zenith pointing with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to air pollution, radiant energy budgets (hence climate), and remote measurements of Earth's surfaces. Direct beam hyperspectral measurement of optical depth improves retrievals of gas constituents and determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution. 4STAR measurements are intended to tighten the closure between satellite and ground-based measurements. 4STAR incorporates a modular sun-tracking/sky-scanning optical head with fiber optic signal transmission to rack mounted spectrometers, permitting miniaturization of the external optical head, and future detector evolution. 4STAR test flights, as well as science flights in the 2012-13 TCAP (Two-Column Aerosol Project) and 2013 SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) have demonstrated that the following are essential for 4STAR to achieve its full science potential: (1) Calibration stability for both direct-beam irradiance and sky radiance, (2) Improved light collection and usage, and (3) Improved flight operability and reliability. A particular challenge for the AITT-4STAR project has been conducting it simultaneously with preparations for, and execution of, ARISE (Arctic Radiation - IceBridge Sea&Ice Experiment), a NASA airborne science deployment (unplanned when AITT-4STAR was selected for funding) in which 4STAR will deploy to Thule, Greenland, and Fairbanks, Alaska, on the NASA C- 130. This presentation describes progress to date in accomplishing AITT-4STAR goals, and plans for project completion.

Sun-Sky-Cloud-Trace↗

A Mesoscale Analysis of Column-Integrated Aerosol Properties in Northern India During the TIGERZ 2008 Pre-Monsoon Period and a Comparison to MODIS Retrievals

The Indo-Gangetic Plain (IGP) of the northern Indian subcontinent produces anthropogenic pollution from urban, industrial and rural combustion sources nearly continuously and is affected by convection-induced winds driving desert and alluvial dust into the atmosphere during the premonsoon period. Within the IGP, the NASA Aerosol Robotic Network (AERONET) project initiated the TIGERZ measurement campaign in May 2008 with an intensive operational period from May 1 to June 23, 2008. Mesoscale spatial variability of aerosol optical depth (AOD, tau) measurements at 500mn was assessed at sites around Kanpur, India, with averages ranging from 0.31 to 0.89 for spatial variability study (SVS) deployments. Sites located downwind from the city of Kanpur indicated slightly higher average aerosol optical depth (delta Tau(sub 500)=0.03-0.09). In addition, SVS AOD area-averages were compared to the long-tenn Kanpur AERONET site data: Four SVS area-averages were within +/- 1 cr of the climatological mean of the Kanpur site, while one SVS was within 2sigma below climatology. For a SVS case using AERONET inversions, the 440-870mn Angstrom exponent of approximately 0.38, the 440-870mn absorption Angstrom exponent (AAE) of 1.15-1.53, and the sphericity parameter near zero suggested the occurrence of large, strongly absorbing, non-spherical aerosols over Kanpur (e.g., mixed black carbon and dust) as well as stronger absorption downwind of Kanpur. Furthermore, the 3km and lOkm Terra and Aqua MODIS C005 aerosol retrieval algorithms at tau(sub 550) were compared to the TIGERZ data set. Although MODIS retrievals at higher quality levels were comparable to the MODIS retrieval uncertainty, the total number of MODIS matchups (N) were reduced with subsequent quality levels (N=25, QA>=0; N=9,QA>=l; N=6, QA>=2; N=1, QA=3) over Kanpur during the premonsoon primarily due to the semi-bright surface, complex aerosol mixture and cloud-contaminated pixels. The TIGERZ 2008 data set provided a unique opportunity to measure the spatial and temporal variations of aerosol loading in the IGP. The strong aerosol absorption derived from ground-based sun/sky radiometer measurements suggested the presence of a predominately black carbon and dust mixture during the pre-monsoon period. Consistent with the elevated heat-pump hypothesis, these absorbing aerosols found across Kanpur and the greater IGP region during the pre-monsoon period likely induced regional atmospheric warming, which lead to a more rapid advance of the southwest Asian monsoon and above normal precipitation over northern India in June 2008.

Giles, D. M.↗

Interpretation of the 6818.9-A methane feature observed on Jupiter, Saturn, and Uranus

High-resolution (0.1-A) spectra of the 6818.9-A methane feature obtained for Jupiter, Saturn, and Uranus by Baines, Schempp, and Smith (1969) are modeled using a doubling and adding code after Hansen (1983). The feature's rotational quantum number is estimated using the relatively homogeneous atmosphere of Saturn, with only J = 0 and J = 1 fitting the observational constraints. The aerosol content within Saturn's northern temperate region is shown to be substantially less than at the equator, indicating a haze only half as optically thick. Models of Jupiter's atmosphere are consistent with the rotational quantum-number assignment. Synthetic line profiles of the 6818.9-A feature observed on Uranus reveal that a substantial haze exists at or above the methane condensation region with an optical depth eight times greater than previously reported. Seasonal effects are indicated. The methane column abundance is 5 + or - 1 km-am. The mixing ratio of methane to hydrogen within the deep unsaturated region of the planet is 0.045 + or - 0.025, based on an H2 column abundance of 240 + or - 60 km-am (Smith, Macy, and Pilcher /1980/), thus indicating that methane comprises between one-sixth and one-half of the planet's mass. However, proper reevaluation of H2 quadrupole features accounting for the haze reported here may significantly reduce the relative methane abundance.

Baines, K. H.↗

Simulations of the Aerosol Index and the Absorption Aerosol Optical Depth and Comparisons with OMI Retrievals During ARCTAS-2008 Campaign

We have computed the Aerosol Index (AI) at 354 nm, useful for observing the presence of absorbing aerosols in the atmosphere, from aerosol simulations conducted with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module running online the GEOS-5 Atmospheric GCM. The model simulates five aerosol types: dust, sea salt, black carbon, organic carbon and sulfate aerosol and can be run in replay or data assimilation modes. In the assimilation mode, information's provided by the space-based MODIS and MISR sensors constrains the model aerosol state. Aerosol optical properties are then derived from the simulated mass concentration and the Al is determined at the OMI footprint using the radiative transfer code VLIDORT. In parallel, model derived Absorption Aerosol Optical Depth (AAOD) is compared with OMI retrievals. We have focused our study during ARCTAS (June - July 2008), a period with a good sampling of dust and biomass burning events. Our ultimate goal is to use OMI measurements as independent validation for our MODIS/MISR assimilation. Towards this goal we document the limitation of OMI aerosol absorption measurements on a global scale, in particular sensitivity to aerosol vertical profile and cloud contamination effects, deriving the appropriate averaging kernels. More specifically, model simulated (full) column integrated AAOD is compared with model derived Al, this way identifying those regions and conditions under which OMI cannot detect absorbing aerosols. Making use of ATrain cloud measurements from MODIS, C1oudSat and CALIPSO we also investigate the global impact on clouds on OMI derived Al, and the extent to which GEOS-5 clouds can offer a first order representation of these effects.

Source record↗

Characterization of Aerosols over the Indochina Peninsula from Satellite-Surface Observations During Biomass Burning Pre-Monsoon Season

This paper presents characterization of aerosols over the Indochina peninsular regions of Southeast Asia during pre-monsoon season from satellite and ground-based radiometric observations. Our analysis focuses on the seasonal peak period in aerosol loading and biomass burning, prior to the onset of the Asian summer monsoon, as observed in the inter-annual variations of Aerosol Optical Depth (AOD) and fire count data from MODIS. Multi-year (2007-2011) analysis of spaceborne lidar measurements, from CALIOP, indicates presence of aerosols mostly within boundary layer, however extending to elevated altitudes to approx. 4 km over northern regions of Indochina, encompassing Myanmar, northern Thailand and southern China. In addition, a strong gradient in aerosol loading and vertical distribution is observed from the relatively clean equatorial conditions to heavy smoke-laden northern regions (greater aerosol extinction and smaller depolarization ratio). Based on column-integrated ground-based measurements from four AERONET locations distributed over Thailand, the regional aerosol loading is found to be significantly absorbing with spectral single scattering albedo (SSA) below 0.91+/-0.02 in the 440-1020 nm range, with lowest seasonal mean SSA (most absorbing aerosol) over the northern location of Chiang Mai (SSA approx. 0.85) during pre-monsoon season. The smoke-laden aerosol loading is found to exhibit a significant diurnal pattern with higher AOD departures during early morning observations relative to late afternoon conditions (peak difference of more than 15% amplitude). Finally, satellite-based aerosol radiative impact is assessed using CERES shortwave Top-of-Atmosphere flux, in conjunction with MODIS AOD. Overall, a consistency in the aerosol-induced solar absorption characteristic is found among selected regions from ground-based sunphotometer-derived spectral SSA retrievals and satellite-based radiative forcing analysis.

Indochina↗

Investigating Drivers of Particulate Matter Pollution Over India and the Implications for Radiative Forcing With GEOS-Chem-TOMAS15

Ambient fine particulate matter (PM 2.5 ) concentrations in India frequently exceed 100 μg/m 3 during fall and winter pollution episodes. We use the GEOS-Chem chemical transport model with the TwO-Moment Aerosol Sectional microphysics scheme with 15 size bins (TOMAS15) to assess PM 2.5 composition and impacts on radiation and cloud condensation nuclei (CCN) during pollution episodes as compared to the seasonal (October-December) average. We conduct high resolution (0.25° × 0.3125°) nested-domain simulations over India for short-duration, high-PM2.5 episodes in the fall of 2015 and 2017. The simulations capture the magnitude and spatial patterns of pollution episodes measured by surface monitors (r PM2.5 = 0.69) although aerosol optical depth is underestimated. During the episodes, near-surface organic matter (OM), black carbon (BC), and secondary inorganic aerosol concentrations increase from seasonal averages by up to 36, 7, and 7 μg/m 3 , respectively. Episodic aerosol increases enhance cooling by lowering the top-of-atmosphere clear-sky direct radiative effect (DRE TOA ) during the 2015 episode (−6 W/m 2 ), with a smaller impact during the 2017 episode (−1 W/m 2 ). Differences in DRE TOA reflect larger increases in scattering aerosols in the column during the 2015 episode (+17 mg/m 2 ) than in 2017 (+13 mg/m 2 ), while absorbing aerosol column enhancements are smaller (+3 mg/m2) in both years. Changes in shortwave radiation at the surface (SW sfc ) are spatially similar to DRE TOA and mostly negative during both episodes. CCN enhancements (0.2% supersaturation) during these episodes occur across the western Indo-Gangetic Plain, coincident with higher PM 2.5 concentrations. Changes in DRE TOA , SW sfc , and CCN during high-PM 2.5 episodes may have implications for crops, the hydrologic cycle, and surface temperature.

PM2.5↗