Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to ...lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism.
This article presents a method within a Bayesian framework for quantifying uncertainty in satellite aerosol remote sensing when retrieving aerosol optical depth (AOD). By using a Bayesian model ...averaging technique, we take into account uncertainty in aerosol optical model selection and also obtain a shared inference about AOD based on the best-fitting optical models. In particular, uncertainty caused by forward-model approximations has been taken into account in the AOD retrieval process to obtain a more realistic uncertainty estimate. We evaluated a model discrepancy, i.e., forward-model uncertainty, empirically by exploiting the residuals of model fits and using a Gaussian process to characterise the discrepancy. We illustrate the method with examples using observations from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite. We evaluated the results against ground-based remote sensing aerosol data from the Aerosol Robotic Network (AERONET).
Satellite instruments provide a vantage point for studying aerosol
loading consistently over different regions of the world. However, the
typical lifetime of a single satellite platform is on the ...order of 5–15 years; thus, for climate studies, the use of multiple satellite sensors
should be considered. Discrepancies exist between aerosol optical depth
(AOD) products due to differences in their information content, spatial and
temporal sampling, calibration, cloud masking, and algorithmic assumptions.
Users of satellite-based AOD time-series are confronted with the challenge
of choosing an appropriate dataset for the intended application. In this
study, 16 monthly AOD products obtained from different satellite sensors and
with different algorithms were inter-compared and evaluated against Aerosol
Robotic Network (AERONET) monthly AOD. Global and regional analyses
indicate that products tend to agree qualitatively on the annual, seasonal
and monthly timescales but may be offset in magnitude. Several approaches
were then investigated to merge the AOD records from different satellites
and create an optimised AOD dataset. With few exceptions, all merging
approaches lead to similar results, indicating the robustness and stability
of the merged AOD products. We introduce a gridded monthly AOD merged
product for the period 1995–2017. We show that the quality of the merged
product is as least as good as that of individual products. Optimal
agreement of the AOD merged product with AERONET further demonstrates the
advantage of merging multiple products. This merged dataset provides a
long-term perspective on AOD changes over different regions of the world,
and users are encouraged to use this dataset.
Abstract
One major source of uncertainty in the cloud-mediated aerosol forcing arises from the magnitude of the cloud liquid water path (LWP) adjustment to aerosol-cloud interactions, which is poorly ...constrained by observations. Many of the recent satellite-based studies have observed a decreasing LWP as a function of cloud droplet number concentration (CDNC) as the dominating behavior. Estimating the LWP response to the CDNC changes is a complex task since various confounding factors need to be isolated. However, an important aspect has not been sufficiently considered: the propagation of natural spatial variability and errors in satellite retrievals of cloud optical depth and cloud effective radius to estimates of CDNC and LWP. Here we use satellite and simulated measurements to demonstrate that, because of this propagation, even a positive LWP adjustment is likely to be misinterpreted as negative. This biasing effect therefore leads to an underestimate of the aerosol-cloud-climate cooling and must be properly considered in future studies.
The spectral dependence of light absorption by atmospheric particulate matter has major implications for air quality and climate forcing, but remains uncertain especially in tropical areas with ...extensive biomass burning. In the September-October 2007 biomass-burning season in Santa Cruz, Bolivia, we studied light absorbing (chromophoric) organic or "brown" carbon (BrC) with surface and space-based remote sensing. We found that BrC has negligible absorption at visible wavelengths, but significant absorption and strong spectral dependence at UV wavelengths. Using the ground-based inversion of column effective imaginary refractive index in the range 305-368 nm, we quantified a strong spectral dependence of absorption by BrC in the UV and diminished ultraviolet B (UV-B) radiation reaching the surface. Reduced UV-B means less erythema, plant damage, and slower photolysis rates. We use a photochemical box model to show that relative to black carbon (BC) alone, the combined optical properties of BrC and BC slow the net rate of production of ozone by up to 18% and lead to reduced concentrations of radicals OH, HO
, and RO
by up to 17%, 15%, and 14%, respectively. The optical properties of BrC aerosol change in subtle ways the generally adverse effects of smoke from biomass burning.
We studied the wavelength‐dependence of the attenuation of incoming solar UV radiation by a homogeneous cloud layer. By systematic analysis of irradiances simulated with a radiative transfer model, ...we were able to separate the wavelength‐dependence of the cloud modification factor into different components, and thus achieve an understanding of the physical processes involved. Our results show that short wavelengths, in general, penetrate the cloud more effectively than longer wavelengths and that there are two important contributors to this wavelength‐dependence: (1) that induced by multiple scattering between the cloud top and the atmosphere above and (2) that introduced by the wavelength‐dependent radiance distribution at the cloud top (including the direct beam) together with the transmittance of the cloud alone as function of angle of incidence. Furthermore, we found that the former does not depend on solar zenith angle, whereas the latter does and hence also introduces a solar zenith angle dependence in the wavelength‐dependence of the cloud modification factor.
In this paper, we present the implementation and evaluation of the
aerosol microphysics module SALSA2.0 in the framework of the
aerosol–chemistry–climate model ECHAM-HAMMOZ. It is an alternative
...microphysics module to the default modal microphysics scheme M7 in
ECHAM-HAMMOZ. The SALSA2.0 implementation within ECHAM-HAMMOZ is evaluated
against observations of aerosol optical properties, aerosol mass, and size
distributions, comparing also to the skill of the M7 implementation. The
largest differences between the implementation of SALSA2.0 and M7 are in the
methods used for calculating microphysical processes, i.e., nucleation,
condensation, coagulation, and hydration. These differences in the
microphysics are reflected in the results so that the largest differences
between SALSA2.0 and M7 are evident over regions where the aerosol size
distribution is heavily modified by the microphysical processing of aerosol
particles. Such regions are, for example, highly polluted regions and regions
strongly affected by biomass burning. In addition, in a simulation of the
1991 Mt. Pinatubo eruption in which a stratospheric sulfate plume was formed,
the global burden and the effective radii of the stratospheric aerosol are
very different in SALSA2.0 and M7. While SALSA2.0 was able to reproduce the
observed time evolution of the global burden of sulfate and the effective
radii of stratospheric aerosol, M7 strongly overestimates the removal of
coarse stratospheric particles and thus underestimates the effective radius
of stratospheric aerosol. As the mode widths of M7 have been optimized for
the troposphere and were not designed to represent stratospheric aerosol, the
ability of M7 to simulate the volcano plume was improved by modifying the
mode widths, decreasing the standard deviations of the accumulation and coarse
modes from 1.59 and 2.0, respectively, to 1.2 similar to what was observed
after the Mt. Pinatubo eruption. Overall, SALSA2.0 shows promise in improving
the aerosol description of ECHAM-HAMMOZ and can be further improved by
implementing methods for aerosol processes that are more suitable for the
sectional method, e.g., size-dependent emissions for aerosol species and size-resolved wet deposition.
We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR ...algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15%) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.
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