Climatology of aerosols over the Caribbean islands: aerosol types, synoptic patterns and transport

We present a climatological study of aerosols in four representative Caribbean islands based on daily mean values of aerosol optical properties for the period 2008- 2016, using the Aerosol Optical Depth (AOD) and Ångström Exponent (AE) to classify the dominant aerosol type. A climatological assessment of the spatio-temporal distribution of the main aerosol types, their links with synoptic patterns and the transport from different sources is provided. Maximum values of AOD occur in the rainy season, coinciding with the minimum in AE and an increased occurrence of dust, while the minimum of AOD occurs in the dry season, due to the predominance of marine aerosols. Marine and dust aerosol are more frequent in the easternmost islands and decrease westwards due to an increasing of continental and mixture dust aerosols. Therefore, the westernmost station displays the most heterogeneous composition of aerosols. Using a weather type classification, we identify a quantifiable influence of the atmospheric circulation in the distribution of Caribbean aerosols. However, they can occur under relatively weak and/or diverse synoptic patterns, typically involving transient systems and specific configurations of the Azores High that depend on the considered station. Backward trajectories indicate that dry-season marine aerosols and rainy-season dust are transported by air parcels travelling within the tropical easterly winds. The main source region for both types of aerosols is the subtropical eastern Atlantic, except for Cuba, where the largest contributor to dry-season marine aerosols is the subtropical western Atlantic. Different aerosol types follow similar pathways, suggesting a key role of emission sources in determining the spatio-temporal distribution of Caribbean aerosols.

Assessing the benefits of Imaging Infrared Radiometer observations to the CALIOP version 4 cloud and aerosol discrimination algorithm

The features detected in monolayer atmospheric columns sounded by the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) and classified as cloud or aerosol layers by the CALIOP version 4 (V4) cloud and aerosol discrimination (CAD) algorithm are reassessed using perfectly collocated brightness temperatures measured by the Imaging Infrared Radiometer (IIR) onboard the same satellite. Using the IIR’s three wavelength measurements of layers that are confidently classified by the CALIOP CAD algorithm, we calculate two-dimensional (2-D) probability distribution functions (PDFs) of IIR brightness temperature differences (BTDs) for different cloud and aerosol types. We then compare these PDFs with 1-D radiative transfer simulations for ice and water clouds and dust and marine aerosols. Using these IIR 2-D BTD signature PDFs, we develop and deploy a new IIR-based CAD algorithm and compare the classifications obtained to the results reported by the CALIOP-only V4 CAD algorithm. IIR observations are shown to be able to identify clouds with a good accuracy. The IIR cloud identifications agree very well with layers classified as confident clouds by the V4 CAD algorithm (88 %). More importantly, simultaneous use of IIR information reduces the ambiguity in a notable fraction of "not confident" V4 cloud classifications. 28 % and 14 % of the ambiguous V4 cloud classifications are confirmed thanks to the IIR observations in the tropics and in the midlatitudes respectively. IIR observations are of relatively little help in deriving high confidence classifications for most aerosols, as the low altitudes and small optical depths of aerosol layers yield IIR signatures that are similar to those from clear skies. However, misclassifications of aerosol layers, such as dense dust or elevated smoke layers, by the V4 CAD algorithm can be corrected to cloud layer classification by including IIR information. 10 %, 16 %, and 6 % of the ambiguous V4 dust, polluted dust, and tropospheric elevated smoke respectively are found to be misclassified cloud layers by the IIR measurements.

Columnar aerosol types and compositions over peninsular Southeast Asia based on long-term AERONET data

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

Assessment of tropospheric CALIPSO Version 4.2 aerosol types over the ocean using independent CALIPSO-SODA lidar ratios

We assess the CALIPSO Version 4.2 (V4) aerosol typing and assigned lidar ratios over ocean using aerosol optical depth (AOD) retrievals from the Synergized Optical Depth of Aerosols (SODA) algorithm and retrieved columnar lidar ratio estimated by combining SODA AOD and CALIPSO attenuated backscatter (CALIPSO-SODA). Six aerosol types – clean marine, dusty marine, dust, polluted continental/smoke, polluted dust, and elevated smoke – are characterized using CALIPSO-SODA over ocean and the results are compared against the prescribed V4 lidar ratios, when only one aerosol type is present in the atmospheric column. For samples detected at 5-km or 20-km spatial resolutions and having AOD > 0.05, the CALIPSO-SODA lidar ratios are significantly different between different aerosol types, and are consistent with the type-specific values assigned in V4 to within 10 sr (except for polluted continental/smoke). This implies that the CALIPSO classification scheme generally categorizes aerosols correctly. We find remarkable daytime/nighttime regional agreement for clean marine aerosol over the open ocean (CALIPSO-SODA = 20–25 sr, V4 = 23 sr), elevated smoke over the southeast Atlantic (CALIPSO-SODA = 65–75 sr, V4 = 70 sr), and dust over the subtropical Atlantic adjacent to the African continent (CALIPSO-SODA = 40–50 sr, V4 = 44 sr). In contrast, daytime polluted continental/smoke lidar ratio is more than 20 sr smaller than the constant V4 vaue for that type, attributed in part to the challenge of classifying tenuous aerosol with low signal-to-noise ratio. Dust over most of the Atlantic Ocean features CALIPSO-SODA lidar ratios less than 40 sr, possibly suggesting the presence of dust mixed with marine aerosols or lidar ratio values that depend on source and evolution of the aerosol plume. The new dusty marine type introduced in V4 features similar magnitudes and spatial distribution as its clean marine counterpart with lidar ratio differences of less than 3 sr, and nearly identical values over the open ocean, implying that some modification of the classification scheme for the marine subtypes is warranted.

What rainfall rates are most important to wet removal of different aerosol types?

Both frequency and intensity of rainfall affect aerosol wet deposition. With a stochastic deep convection scheme implemented into two state-of-the-art global climate models (GCMs), a recent study found that aerosol burdens are increased globally by reduced climatological mean wet removal of aerosols due to suppressed light rain. Motivated by their work, a novel approach is developed in this study to detect what rainfall rates are most efficient for wet removal (scavenging amount mode) of different aerosol species of different sizes in GCMs and applied to the National Center for Atmospheric Research Community Atmosphere Model version 5 (CAM5) with and without the stochastic convection cases. Results show that in the standard CAM5, no obvious differences in the scavenging amount mode are found among different aerosol types. However, the scavenging amount modes differ in the Aitken, accumulation and coarse modes, showing around 10–12, 8–9 and 7–8 mm d−1, respectively, over the tropics. As latitude increases poleward, the scavenging amount mode in each aerosol mode is decreased substantially. The scavenging amount mode is generally smaller over land than over ocean. With stochastic convection, the scavenging amount mode for all aerosol species in each mode is systematically increased, which is the most prominent along the Intertropical Convergence Zone, exceeding 20 mm d−1 for small particles. The scavenging amount modes in the two cases are both smaller than individual rainfall rates associated with the most accumulated rain (rainfall amount mode), further implying precipitation frequency is more important than precipitation intensity for aerosol wet removal. The notion of the scavenging amount mode can be applied to other GCMs to better understand the relation between rainfall and aerosol wet scavenging, which is important to better simulate aerosols.

Background Optical Depth Correction over Urban Areas to Improve Land Aerosol Retrieval from Himawari-8

A conventional clear-sky minimum reflectance method, which has been widely used for AOD retrieval from geostationary satellites, usually has less accuracy over urban than other land areas. Urban areas usually have more complex surface properties and various aerosol types from different emission sources. When the surface reflectance is calculated from the clear-sky minimum reflectance, background aerosol optical depth (BOD) is assumed to be closed to zero. This assumption generates larger surface reflectance which leads to underestimation of AOD retrieved. This study proposed a correction for BOD value to be applied for AOD retrieval primary over urban areas where the pollution or natural source aerosol is persistent for long term. The study area covers Indonesia’s land region, while for evaluating the impact of specific treatment over urban areas we used the AERONET data from Bandung, Pontianak, and Makassar sites. The comparison of AOD retrieved from modified BOD and the AERONET ground-based data showed that the corrected surface reflectance improved the accuracy of AOD in the three sites, with a correlation coefficient increased from 0.23 to 0.37 and the fraction of ‘good retrieval’ changed from 35% to 51%.

Bayesian uncertainty quantification in aerosol optical depth retrieval applied to TROPOMI measurements

We present here an aerosol model selection based statistical method in Bayesian framework for retrieving atmospheric aerosol optical depth (AOD) and pixel-level uncertainty. Especially, we focus on to provide more realistic uncertainty estimate by taking into account a model selection problem when searching for the solution by fitting look-up table (LUT) models to a satellite measured top-of-atmosphere reflectance. By means of Bayesian model averaging over the best-fitting aerosol models we take into account an aerosol model selection uncertainty and get also a shared inference about AOD. Moreover, we acknowledge model discrepancy, i.e. forward model error, arising from approximations and assumptions done in forward model simulations. We have estimated the model discrepancy empirically by a statistical approach utilizing residuals of model fits. We use the measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor in ultraviolet and visible bands, and in one wavelength band 675 nm in near-infrared, in order to study the functioning of the retrieval in a broad wavelength range. We exploit a fundamental classification of the aerosol models as weakly absorbing, biomass burning and desert dust aerosols. For experimental purpose we have included some dust type of aerosols having non-spherical particle shapes. For this study we have created the aerosol model LUTs with radiative transfer simulations using the libRadtran software package. It is reasonably straightforward to experiment with different aerosol types and evaluate the most probable aerosol type by the model selection method. We demonstrate the method in wildfire and dust events in a pixel level. In addition, we have evaluated in detail the results against ground-based remote sensing data from the AErosol RObotic NETwork (AERONET). Based on the case studies the method has ability to identify the appropriate aerosol types, but in some wildfire cases the AOD is overestimated compared to the AERONET result. The resulting uncertainty when accounting for the model selection problem and the imperfect forward modelling is higher compared to uncertainty when only measurement error is included in an observation model, as can be expected.

Identification of Smoke and Sulfuric Acid Aerosol in SAGE III/ISS Extinction Spectra Following the 2019 Raikoke Eruption

The 2019 eruption of Raikoke was the largest volcanic eruption since 2011 and it was coincident with 2 major wildfires in the northern hemisphere. The impact of these events was manifest in the SAGE III/ISS extinction coefficient measurements. As the volcanic aerosol layers moved southward, a secondary peak emerged at an altitude higher than that which is expected for sulfuric acid aerosol. It was hypothesized that this secondary plume may contain a non-negligible amount of smoke contribution. We developed a technique to classify the composition of enhanced aerosol layers as either smoke or sulfuric acid aerosol. This method takes advantage of the different spectral properties of smoke and sulfuric acid aerosol, which is manifest in distinctly different spectral slopes in the SAGE III/ISS data. Herein we demonstrate the utility of this method using 4 case-study events (2018 Ambae eruption, 2019 Ulawun eruption, 2017 Canadian pyroCb, and 2020 Australian pyroCb) and provide corroborative data from the CALIOP instrument before applying it to the Raikoke plumes. We determined that, in the time period following the Raikoke eruption, smoke and sulfuric acid aerosol were present throughout the atmosphere and the 2 aerosol types were preferentially partitioned to higher (smoke) and lower (sulfuric acid) altitudes. Herein, we present an evaluation of the performance of this classification scheme within the context of the aforementioned case-study events followed by a brief discussion of this method's applicability to other events as well as its limitations.

Ambient aerosol properties in the remote atmosphere from global-scale in situ measurements

In situ measurements of aerosol microphysical, chemical, and optical properties were made during global-scale flights from 2016–2018 as part of the Atmospheric Tomography Mission (ATom). The NASA DC-8 aircraft flew from ∼ 84∘ N to ∼ 86∘ S latitude over the Pacific, Atlantic, Arctic, and Southern oceans while profiling nearly continuously between altitudes of ∼ 160 m and ∼ 12 km. These global circuits were made once each season. Particle size distributions measured in the aircraft cabin at dry conditions and with an underwing probe at ambient conditions were combined with bulk and single-particle composition observations and measurements of water vapor, pressure, and temperature to estimate aerosol hygroscopicity and hygroscopic growth factors and calculate size distributions at ambient relative humidity. These reconstructed, composition-resolved ambient size distributions were used to estimate intensive and extensive aerosol properties, including single-scatter albedo, the asymmetry parameter, extinction, absorption, Ångström exponents, and aerosol optical depth (AOD) at several wavelengths, as well as cloud condensation nuclei (CCN) concentrations at fixed supersaturations and lognormal fits to four modes. Dry extinction and absorption were compared with direct in situ measurements, and AOD derived from the extinction profiles was compared with remotely sensed AOD measurements from the ground-based Aerosol Robotic Network (AERONET); this comparison showed no substantial bias. The purpose of this work is to describe the methodology by which ambient aerosol properties are estimated from the in situ measurements, provide statistical descriptions of the aerosol characteristics of different remote air mass types, examine the contributions to AOD from different aerosol types in different air masses, and provide an entry point to the ATom aerosol database. The contributions of different aerosol types (dust, sea salt, biomass burning, etc.) to AOD generally align with expectations based on location of the profiles relative to continental sources of aerosols, with sea salt and aerosol water dominating the column extinction in most remote environments and dust and biomass burning (BB) particles contributing substantially to AOD, especially downwind of the African continent. Contributions of dust and BB aerosols to AOD were also significant in the free troposphere over the North Pacific. Comparisons of lognormally fitted size distribution parameters to values in the Optical Properties of Aerosols and Clouds (OPAC) database commonly used in global models show significant differences in the mean diameters and standard deviations for accumulation-mode particles and coarse-mode dust. In contrast, comparisons of lognormal parameters derived from the ATom data with previously published shipborne measurements in the remote marine boundary layer show general agreement. The dataset resulting from this work can be used to improve global-scale representation of climate-relevant aerosol properties in remote air masses through comparison with output from global models and assumptions used in retrievals of aerosol properties from both ground-based and satellite remote sensing.

Global Clear-Sky Aerosol Speciated Direct Radiative Effects over 40 Years (1980–2019)

We assess the 40-year climatological clear-sky global direct radiative effect (DRE) of five main aerosol types using the MERRA-2 reanalysis and a spectral radiative transfer model (FORTH). The study takes advantage of aerosol-speciated, spectrally and vertically resolved optical properties over the period 1980–2019, to accurately determine the aerosol DREs, emphasizing the attribution of the total DREs to each aerosol type. The results show that aerosols radiatively cool the Earth’s surface and heat its atmosphere by 7.56 and 2.35 Wm−2, respectively, overall cooling the planet by 5.21 Wm−2, partly counterbalancing the anthropogenic greenhouse global warming during 1980–2019. These DRE values differ significantly in terms of magnitude, and even sign, among the aerosol types (sulfate and black carbon aerosols cool and heat the planet by 1.88 and 0.19 Wm−2, respectively), the hemispheres (larger NH than SH values), the surface cover type (larger land than ocean values) or the seasons (larger values in local spring and summer), while considerable inter-decadal changes are evident. These DRE differences are even larger by up to an order of magnitude on a regional scale, highlighting the important role of the aerosol direct radiative effect for local and global climate.