Abstract. The Aerosol Robotic Network (AERONET) has provided highly
accurate, ground-truth measurements of the aerosol optical depth (AOD) using
Cimel Electronique Sun–sky radiometers for more than 25 years. In Version 2 (V2)
of the AERONET database, the near-real-time AOD was semiautomatically
quality controlled utilizing mainly cloud-screening methodology, while
additional AOD data contaminated by clouds or affected by instrument
anomalies were removed manually before attaining quality-assured status
(Level 2.0). The large growth in the number of AERONET sites over the past
25 years resulted in significant burden to the manual quality control of millions
of measurements in a consistent manner. The AERONET Version 3 (V3) algorithm
provides fully automatic cloud screening and instrument anomaly quality
controls. All of these new algorithm updates apply to near-real-time data as
well as post-field-deployment processed data, and AERONET reprocessed the
database in 2018. A full algorithm redevelopment provided the opportunity to
improve data inputs and corrections such as unique filter-specific
temperature characterizations for all visible and near-infrared wavelengths,
updated gaseous and water vapor absorption coefficients, and ancillary data
sets. The Level 2.0 AOD quality-assured data set is now available within a
month after post-field calibration, reducing the lag time from up to several
months. Near-real-time estimated uncertainty is determined using data
qualified as V3 Level 2.0 AOD and considering the difference between the AOD
computed with the pre-field calibration and AOD computed with pre-field and
post-field calibration. This assessment provides a near-real-time
uncertainty estimate for which average differences of AOD suggest a +0.02 bias
and one sigma uncertainty of 0.02, spectrally, but the bias and uncertainty
can be significantly larger for specific instrument deployments. Long-term
monthly averages analyzed for the entire V3 and V2 databases produced
average differences (V3–V2) of +0.002 with a ±0.02 SD (standard
deviation), yet monthly averages calculated using time-matched observations
in both databases were analyzed to compute an average difference of −0.002
with a ±0.004 SD. The high statistical agreement in
multiyear monthly averaged AOD validates the advanced automatic data
quality control algorithms and suggests that migrating research to the
V3 database will corroborate most V2 research conclusions and likely lead to
more accurate results in some cases.
Measurements and models show that enhanced aerosol concentrations can augment cloud albedo not only by increasing total droplet cross-sectional area, but also by reducing precipitation and thereby increasing cloud water content and cloud coverage. Aerosol pollution is expected to exert a net cooling influence on the global climate through these conventional mechanisms. Here, we demonstrate an opposite mechanism through which aerosols can reduce cloud cover and thus significantly offset aerosol-induced radiative cooling at the top of the atmosphere on a regional scale. In model simulations, the daytime clearing of trade cumulus is hastened and intensified by solar heating in dark haze (as found over much of the northern Indian Ocean during the northeast monsoon).
For 26 days in mid‐June and July 2000, a research group comprised of U.S. Navy, NASA, and university scientists conducted the Puerto Rico Dust Experiment (PRIDE). In this paper we give a brief overview of mean meteorological conditions during the study. We focus on our findings on African dust transported into the Caribbean utilizing a Navajo aircraft and AERONET Sun photometer data. During the study midvisible aerosol optical thickness (AOT) in Puerto Rico averaged 0.25, with a maximum >0.5 and with clean marine periods of ∼0.08. Dust AOTs near the coast of Africa (Cape Verde Islands and Dakar) averaged ∼0.4, 30% less than previous years. By analyzing dust vertical profiles in addition to supplemental meteorology and MPLNET lidar data we found that dust transport cannot be easily categorized into any particular conceptual model. Toward the end of the study period, the vertical distribution of dust was similar to the commonly assumed Saharan Air Layer (SAL) transport. During the early periods of the study, dust had the highest concentrations in the marine and convective boundary layers with only a weak dust layer in the SAL being present, a state usually associated with wintertime transport patterns. We corroborate the findings of Maring et al. [2003] that in most cases, there was an unexpected lack of vertical stratification of dust particle size. We systematically analyze processes that may impact dust vertical distribution and speculate that dust vertical distribution predominately influenced by flow patterns over Africa and differential advection coupled with fair weather cloud entrainment, mixing by easterly waves, and regional subsidence.
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