UMBC Joint Center for Earth Systems Technology (JCET)

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The Joint Center for Earth Systems Technology (JCET) was formed under a Cooperative agreement between the Earth Science Division of NASA Goddard Space Flight Center (GSFC) and the University of Maryland, Baltimore County (UMBC) in 1995. The JCET family consists of its business staff, students, research faculty, GSFC Sponsors, appointed fellows and affiliated tenured/tenure-track faculty. JCET is an innovative center where these scientists interact in a seamless fashion with the support of an efficient business and administrative unit.

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Scientific impact of MODIS C5 calibration degradation and C6+ improvements
(EGU, 2014-12-10) Lyapustin, A.; Wang, Yujie; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, Sergey; Hilker, T.; Tucker, J.; Hall, Forrest G.; Sellers, P.; Wu, A.; Angal, A.
The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra–Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1–B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.
Phase matrix characterization of long-range transported Saharan dust using multiwavelength polarized polar imaging nephelometry
(EGU, 2024-08-14) Bazo, Elena; Perez-Ramirez, Daniel; Valenzuela, Antonio; Martins, J. Vanderlei; Titos, Gloria; Cazorla, Alberto; Rejano, Fernando; Patrón, Diego; Diaz-Zurita, Arlett; Garcia-Izquierdo, Francisco Jose; Fuertes, David; Alados-Arboledas, Lucas; Olmo, Francisco Jose
This work investigates the scattering matrix elements during different Saharan dust outbreaks over Granada (South-East Spain) in 2022 using the Polarized Imaging Nephelometer (PI-Neph PIN100, GRASP-Earth). The PI-Neph is a unique instrument capable of measuring continuously the phase function and polarized phase function (F₁₁ and -F₁₂/F₁₁) at three different wavelengths (405, 515 and 660 nm) with 1° resolution. Extreme dust events (PM₁₀ concentration above 1000 µgm⁻³) occurring in March 2022 are compared with more frequent and moderate events registered in summer 2022 (PM₁₀ concentration between 50 and 100 µgm⁻³). For F₁₁ there are no remarkable differences between extreme and moderate events. However, results of -F₁₂/F₁₁ show large differences between extreme and moderate events, especially for the 405 nm wavelength. These differences are also observed when studying the temporal evolutions during the extreme events and reveal that -F₁₂/F₁₁ patterns similar to laboratory measurements occurred during the more intense periods of dust influence. Other aerosol optical properties were derived from the PI-Neph, such as the asymmetry parameter (g), the fraction of backscattered light (Bs) and the lidar ratio (LR). In general, g and Bs show typical values (g > 0.65 and Bs ~ 0.1) for both extreme and moderate Saharan dust events. However, the LR shows more variable values for the different dust events, ranging from 20 to 60 sr⁻¹. The combination with additional in-situ instrumentation allowed to obtain scattering (SAE) and absorption (AAE) Ångström exponents and to conduct a typing classification that revealed extreme dust events as pure dust while moderate dust events were classified as a mixture of dust with urban background pollution. In addition, model simulations with the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) code reproduce well the PI-Neph measurements. Therefore, our results confirm that differences in the phase matrix elements of Saharan dust outbreaks of varying intensity can be explained by the mixing conditions of dust with the background particles, which varies from almost pure dust particles during extreme events, to a mixture of dust with local pollution during moderate events.
SORD: A New Open Source Vector RT Code
(2024-08-19) Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent
Multiangle implementation of atmospheric correction (MAIAC): 1. Radiative transfer basis and look-up tables
(AGU, 2011-02-11) Lyapustin, Alexei; Martonchik, John; Wang, Yujie; Laszlo, Istvan; Korkin, Sergey
This paper describes a radiative transfer basis of the algorithm MAIAC which performs simultaneous retrievals of atmospheric aerosol and bidirectional surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). The retrievals are based on an accurate semianalytical solution for the top-of-atmosphere reflectance expressed as an explicit function of three parameters of the Ross–Thick Li–Sparse model of surface bidirectional reflectance. This solution depends on certain functions of atmospheric properties and geometry which are precomputed in the look-up table (LUT). This paper further considers correction of the LUT functions for variations of surface pressure/height and of atmospheric water vapor, which is a common task in the operational remote sensing. It introduces a new analytical method for the water vapor correction of the multiple-scattering path radiance. It also summarizes the few basic principles that provide a high efficiency and accuracy of the LUT-based radiative transfer for the aerosol/surface retrievals and optimize the size of LUT. For example, the single-scattering path radiance is calculated analytically for a given surface pressure and atmospheric water vapor. The same is true for the direct surface-reflected radiance, which along with the single-scattering path radiance largely defines the angular dependence of measurements. For these calculations, the aerosol phase functions and kernels of the surface bidirectional reflectance model are precalculated at a high angular resolution. The other radiative transfer functions depend rather smoothly on angles because of multiple scattering and can be calculated at coarser angular resolution to reduce the LUT size. At the same time, this resolution should be high enough to use the nearest neighbor geometry angles to avoid costly three-dimensional interpolation. The pressure correction is implemented via linear interpolation between two LUTs computed for the standard and reduced pressure levels. A linear mixture and a modified linear mixture methods are used to represent different aerosol types in the aerosol/surface retrievals from several base models of the fine and coarse aerosol fractions. In summary, the developed LUT algorithm allows fast high-accuracy simulations of the outgoing radiance with full variability of the atmospheric and surface bidirectional reflectance properties for the aerosol/surface remote sensing.
A new code SORD for simulation of polarized light scattering in the Earth atmosphere
(SPIE, 2016-05-04) Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent
We report a new publicly available radiative transfer (RT) code for numerical simulation of polarized light scattering in plane-parallel Earth atmosphere. Using 44 benchmark tests, we prove high accuracy of the new RT code, SORD (Successive ORDers of scattering¹,²). We describe capabilities of SORD and show run time for each test on two different machines. At present, SORD is supposed to work as part of the Aerosol Robotic NETwork³ (AERONET) inversion algorithm. For natural integration with the AERONET software, SORD is coded in Fortran 90/95. The code is available by email request from the corresponding (first) author or from ftp://climate1.gsfc.nasa.gov/skorkin/SORD/ or ftp://maiac.gsfc.nasa.gov/pub/SORD.zip
MAIAC Status
(NTRS, 2016-06-08) Lyapustin, Alexei; Wang, Yujie; Korkin, Sergey
Performance of the dot product function in radiative transfer code SORD
(SPIE, 2016-10-24) Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent
The successive orders of scattering radiative transfer (RT) codes frequently call the scalar (dot) product function. In this paper, we study performance of some implementations of the dot product in the RT code SORD using 50 scenarios for light scattering in the atmosphere-surface system. In the dot product function, we use the unrolled loops technique with different unrolling factor. We also considered the intrinsic Fortran functions. We show results for two machines: ifort compiler under Windows, and pgf90 under Linux. Intrinsic DOT_PRODUCT function showed best performance for the ifort. For the pgf90, the dot product implemented with unrolling factor 4 was the fastest.The RT code SORD together with the interface that runs all the mentioned tests are publicly available from ftp://maiac.gsfc.nasa.gov/pub/skorkin/SORD_IP_16B (current release) or by email request from the corresponding (first) author.
Accuracy of RT code SORD for realistic atmospheric profiles
(SPIE, 2016-12-14) Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent
We discuss accuracy of our recently developed RT code SORD using 2 benchmark scenarios published by the IPRT group in 2015. These scenarios define atmospheres with a complicate dependence of scattering and absorption properties over height (profile). Equal step, dh=1km, is assumed in the profiles. We developed subroutines that split such atmospheres into layers of the same optical thickness, dτ. We provide full text of the subroutines with comments in Appendix. The dτ is a step for vertical integration in the method of successive orders. Modification of the input profiles from “equal step over h” to “equal step over τ” changes input for RT simulations. This may cause errors at or above the acceptable level of the measurement uncertainty. We show errors of the RT code SORD for both intensity and polarization. In addition to that, using our discrete ordinates RT code IPOL, we discuss one more IPRT scenario, in which changes in height profile indeed cause unacceptable errors. Clear understanding of source and magnitude of these errors is important, e.g. for the AERONET retrieval algorithm.
Multiangle implementation of atmospheric correction (MAIAC): 2. Aerosol algorithm
(AGU, 2011-02-11) Lyapustin, Alexei; Wang, Yujie; Laszlo, I.; Kahn, R.; Korkin, Sergey; Remer, L.; Levy, R.; Reid, J. S.
An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 μm) and shortwave infrared (2.1 μm) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.
Adapting MAIAC Algorithm for Synergistic ABI-TEMPO Processing
(2017-09-11) Lyapustin, Alexei; Torres, Omar; Wang, Yujie; Korkin, Sergey
Reduction of aerosol absorption in Beijing since 2007 from MODIS and AERONET
(AGU, 2011-05-20) Lyapustin, Alexei; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.; Tanré, D.; Dubovik, O.; Goloub, P.; Chen, H.-B.; Sinyuk, A.; Wang, Yujie; Korkin, Sergey
An analysis of the time series of MODIS-based and AERONET aerosol records over Beijing reveals two distinct periods, before and after 2007. The MODIS data from both the Terra and Aqua satellites were processed with the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. A comparison of MAIAC and AERONET AOT shows that whereas MAIAC consistently underestimated peak AOT values by 10–20% in the prior period, the bias mostly disappears after mid-2007. Independent analysis of the AERONET dataset reveals little or no change in the effective radii of the fine and coarse fractions and of the Ångström exponent. At the same time, it shows an increasing trend in the single scattering albedo, by ∼0.02 in 9 years. As MAIAC was using the same aerosol model for the entire 2000–2010 period, the decrease in AOT bias after 2007 can be explained only by a corresponding decrease of aerosol absorption caused by a reduction in local black carbon emissions. The observed changes correlate in time with the Chinese government's broad measures to improve air quality in Beijing during preparations for the Summer Olympics of 2008.
High spatial resolution aerosol retrieval with MAIAC: Application to mountain regions
(AGU, 2011-12-15) Emili, E.; Lyapustin, A.; Wang, Yujie; Popp, C.; Korkin, Sergey; Zebisch, M.; Wunderle, S.; Petitta, M.
Aerosol spatial distribution in populated mountain areas is very heterogeneous and often characterized by scales of variability of several kilometers. Satellites provide an effective tool to map aerosols on an operational basis, but most of the aerosol products intended for continental/global applications have a coarse spatial resolution (10–18 km). The Multiangle Implementation of Atmospheric Correction (MAIAC) is a recently developed algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS), which provides Aerosol Optical Depth (AOD) at a high resolution of 1 km. We analyze the quality and potential of MAIAC AOD in the Alpine region and we derive high resolution AOD maps for the years 2008 and 2009. Cloudiness and snow in mountain regions occasionally lead to an overestimation of AOD due to unresolved cloud and snow pixel contamination. Therefore, we developed a filter that almost preserves the spatial resolution of the product to ensure the good accuracy of MAIAC AOD for air-quality and climatological applications. The AOD is validated with AERONET measurements in the region and compared to the standard MODIS AOD product (MOD04). Similar accuracies are found for both products (RMSE = 0.05) but with MAIAC providing about 50% more observations at the examined locations, because of its higher spatial resolution and less restrictive filtering. Comparison with ground measurements of aerosol mass (PM₁₀) shows that MAIAC AOD can be used to detect the fine scales of aerosol variability (2–3 km) in the mountains. Finally, AOD maps for the Alpine region demonstrate that topography is correlated with the average aerosol spatial distribution.
Analysis of MAIAC dust aerosol retrievals from MODIS over North Africa
(Accademia Peloritana dei Pericolanti, 2011-09-15) Lyapustin, A.; Wang, Yujie; Hsu, C.; Torres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, Sergey
An initial comparison of aerosol optical thickness over North Africa for year 2007 was performed between the Deep Blue (DB) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms complimeted with MISR and OMI data. The dust retrievals are performed using the model of spheroids. The new MAIAC algorithm has a better sensitivity to the small dust storms than the DB algorithm, but it also has biases in the brightest desert regions indicating the need for improvement. The quarterly averaged AOT values in the Bodele depression and western downwind transport region show a good agreement among MAIAC, MISR and OMI data, while the DB algorithm shows a somewhat different seasonality.
Discrimination of biomass burning smoke and clouds in MAIAC algorithm
(EGU, 2012-10-24) Lyapustin, A.; Korkin, Sergey; Wang, Yujie; Quayle, B.; Laszlo, I.
The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the "smoke test" to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 μm as compared to 0.47–0.67 μm due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.
Improved cloud and snow screening in MAIAC aerosol retrievals using spectral and spatial analysis
(EGU, 2012-04-27) Lyapustin, A.; Wang, Yujie; Laszlo, I.; Korkin, Sergey
An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.
Multi-angle implementation of atmospheric correction for MODIS (MAIAC): 3. Atmospheric correction
(Elsevier, 2012-09-29) Lyapustin, Alexei I.; Wang, Yujie; Laszlo, Istvan; Hilker, Thomas; Hall, Forrest G.; Sellers, Piers J.; Tucker, Compton J.; Korkin, Sergey
This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16days of MODIS data gridded to 1km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.
Adjustments to climate perturbations -mechanisms, implications, observational constraints
(2024-07-18) Quaas, Johannes; Andrews, Timothy; Bellouin, Nicolas; Block, Karoline; Boucher, Olivier; Ceppi, Paulo; Dagan, Guy; Doktorowski, Sabine; Eichholz, Hannah Marie; Forster, Piers; Goren, Tom; Gryspeerdt, Edward; Hodnebrog, Øivind; Jia, Hailing; Kramer, Ryan; Lange, Charlotte; Maycock, Amanda C.; Mülmenstädt, Johannes; Myhre, Gunnar; O'connor, Fiona M.; Pincus, Robert; Samset, Bjørn Hallvard; Senf, Fabian; Shine, Keith P.; Smith, Chris; Stjern, Camilla Weum; Takemura, Toshihiko; Toll, Velle; Wall, Casey J.
Since the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global-mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change.
HARP2 Pre-Launch Calibration Overview: The Effects of a Wide Field of View
(EGU, 2024-07-18) Sienkiewicz, Noah; Martins, J. Vanderlei; McBride, Brent; Xu, Xiaoguang; Puthukkudy, Anin; Smith, Rachel; Fernandez-Borda, Roberto
The HyperAngular Rainbow Polarimeter (HARP2) is a wide field-of-view (FOV) polarimeter built for the NASA Plankton Aerosol Cloud and Ocean Ecosystem mission launched in early 2024. HARP2 measures the linear Stokes parameters across a 114° × 100° (along-track by cross-track) FOV. In the Fall of 2022, HARP2 underwent calibration at NASA Goddard Space Flight Center (GSFC) Calibration Laboratory (Code 618). HARP2 was characterized for radiometric and polarimetric response across its FOV. We have used telecentric calibration methodology on prior iterations of HARP that involved the normalization of pixels across the FOV such that calibration parameters determined at the center of the charged coupled device (CCD) detector can be used across the entire scene. By using a dual-axis yaw/pitch motorized mount, we devised two scan patterns to evaluate this methodology for HARP2. The results show that pure intensity measurements do indeed vary minimally across the FOV and therefore can utilize the flat-field normalization (telecentric) technique. On the other hand, images of polarized targets change significantly across the FOV, and calibration parameters determined at the center of the detector used in the wide FOV perform significantly worse than calibration parameters determined at or near to the location of the test (up to 5 % mean absolute error in degree of linear polarization, DoLP). We evaluated the use of a paraboloid fit of the polarized calibration parameters, at discrete FOV locations, to determine those parameters at a pixel-level resolution. According to the wide FOV results, this process shows a marked improvement for fully polarized (DoLP = 1) calibration data to less than 1 % uncertainty after using the paraboloid fit. These results are important for the development of any wide FOV polarimeter, especially those like HARP2 which use a front lens which causes significant barrel distortion and a division of amplitude central optical element leveraging multiple reflections. Full characterization of the source of these optical effects remains a part of future work.
Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and Central Africa
(2024-05-16) Choi, Myungje; Lyapustin, Alexei; Schuster, Gregory L.; Go, Sujung; Wang, Yujie; Korkin, Sergey; Kahn, Ralph; Reid, Jeffrey S.; Hyer, Edward J.; Eck, Thomas F.; Chin, Mian; Diner, David J.; Kalashnikova, Olga; Dubovik, Oleg; Kim, Jhoon; Moosmüller, Hans
Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke’s effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, black carbon (BC) and brown carbon (BrC) aerosols. Using NASA’s Earth Polychromatic Imaging Camera (EPIC) instrument aboard the NOAA’s Deep Space Climate Observatory (DSCOVR) spacecraft, we inferred BC and BrC volume fractions and particle mass concentrations based on spectral absorption provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm with 1–2 hours temporal resolution and ~10 km spatial resolution over North America and Central Africa. Our analyses of regional smoke properties reveal distinct characteristics for aerosol optical depth (AOD) at 443 nm, spectral single scattering albedo (SSA), aerosol layer height (ALH), and BC and BrC amounts. Smoke cases in North America show extremely high AOD up to 6, with elevated ALH (6–7 km) and significant BrC components up to 250 mg/m² along the transport paths, whereas the smoke aerosols in Central Africa exhibited stronger light absorption (i.e., lower SSA) and lower AOD, resulting in higher BC mass concentrations and similar BrC mass concentrations than the cases in North America. Seasonal burning source locations in Central Africa following the seasonal shift of Inter Tropical Convergence Zone and diurnal variations in smoke amounts were also captured. Comparison of retrieved AOD₄₄₃, SSA₄₄₃, SSA₆₈₀, and ALH with collocated AERONET and CALIOP measurements shows agreement with rmse of 0.2, 0.03–0.04, 0.02–0.04, and 0.8–1.3 km, respectively. Analysis of spatiotemporally average reveals distinct geographical characteristics in smoke properties closely linked to burning types and meteorological conditions. Forest wildfires over western North America generated smoke with small BC volume fraction of 0.011 and high ALH with large variability (2.2 ± 1.2 km), whereas smoke from wildfires and agricultural burning over Mexico region shows more absorption and low ALH. Smoke from savanna fires over Central Africa has the most absorption with high BC volume fraction (0.015) and low ALH with small variation (1.8 ± 0.6 km) among the analyzed regions. Tropical forest smoke was less absorbing and had a high variance in ALH. We also quantify the estimation uncertainties related to the assumptions of BC and BrC refractive indices. The MAIAC EPIC smoke properties with BC and BrC volume and mass fractions and assessment of layer height provide observational constraints for radiative forcing modeling and air quality and health studies.
Multi-scale observations of mangrove blue carbon ecosystem fluxes: The NASA Carbon Monitoring System BlueFlux field campaign
(IOP, 2023-07-10) Poulter, Benjamin; Adams-Metayer, Francis M.; Amaral, Cibele; Barenblitt, Abigail; Campbell, Anthony D.; Charles, Sean P.; Roman-Cuesta, Rosa Maria; D’Ascanio, Rocco; Delaria, Erin R.; Doughty, Cheryl; Fatoyinbo, Temilola; Gewirtzman, Jonathan; Hanisco, Thomas F.; Hull, Moshema; Kawa, S. Randy; Hannun, Reem; Lagomasino, David; Lait, Leslie; Malone, Sparkle L.; Newman, Paul A.; Raymond, Peter; Rosentreter, Judith A.; Thomas, Nathan; Vaughn, Derrick; Wolfe, Glenn; Xiong, Lin; Ying, Qing; Zhang, Zhen
The BlueFlux field campaign, supported by NASA’s Carbon Monitoring System, will develop prototype blue carbon products to inform coastal carbon management. While blue carbon has been suggested as a nature-based climate solution (NBS) to remove carbon dioxide (CO₂) from the atmosphere, these ecosystems also release additional greenhouse gases (GHGs) such as methane (CH₄) and are sensitive to disturbances including hurricanes and sea-level rise. To understand blue carbon as an NBS, BlueFlux is conducting multi-scale measurements of CO₂ and CH₄ fluxes across coastal landscapes, combined with long-term carbon burial, in Southern Florida using chambers, flux towers, and aircraft combined with remote-sensing observations for regional upscaling. During the first deployment in April 2022, CO₂ uptake and CH₄ emissions across the Everglades National Park averaged -4.9 ± 4.7 µmol CO₂ m⁻² s⁻¹ and 19.8 ± 41.1 nmol CH4 m⁻² s⁻¹, respectively. When scaled to the region, mangrove CH₄ emissions offset the mangrove CO₂ uptake by about 5% (assuming a 100 year CH₄ global warming potential of 28), leading to total net uptake of 31.8 Tg CO₂-eq y⁻¹. Subsequent field campaigns will measure diurnal and seasonal changes in emissions and integrate measurements of long-term carbon burial to develop comprehensive annual and long-term GHG budgets to inform blue carbon as a climate solution.

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