Seasonal and interannual assessment of cloud cover and atmospheric constituents across the Amazon (2000–2015): Insights for remote sensing and climate analysis

Abstract

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (>80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon-unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g cm−2) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content (∼0.3 g/cm2) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface obs...

Analysis of cloud condition on Sentinel-2 MSI and Landsat-8 OLI images of a public supply lake in Belém-Pará-Brazil

“…We found around one useful scene per month of the Bolonha Lake (October 2016, March, April and May 2017 and March 2018 were the only months with no usable image found). This implies that the monitoring of aquatic environments using S-2 MSI and L-8 OLI imagery data is feasible even under the inherent excessive cloud regime of the Amazon (Martins et al, 2018). The results of the PCA of the first (78.6%) and second (21.4%) components, suitable S-2 MSI and L-8 OLI data and total satellite available data, respectively, pointed out three different groups (Figure 3).…”

“…In this context, remote sensing (RS) data and techniques offer a feasible means to explore spatial and temporal information, bringing a variety of insights related to tropical ecosystems (Martins et al, 2018;Yang et al, 2013). Among the RS possibilities for water quality monitoring, it is relevant to mention the use of open source data, such as Sentinel-2 Multispectral Instrument (S-2 MSI) and Landsat-8 Operational Land Imager (L-8 OLI) (Pahlevan et al, 2017;2019), which we used in the analysis of this paper.…”

“…Landsat historical series also offers the opportunity to analyse the ecological regime of floating macrophyte greenness throughout vegetation indexes (Terborgh et al, 2018). However, in the Amazon, the seasonal variability of the main atmospheric constituents represents a challenge for optical RS (e.g., cloudiness regime, the high aerosol burden in the dry season, among others) (Martins et al, 2018).…”

Satellite mapping of PM<sub>2.5</sub> episodes in the wintertime San Joaquin Valley: a “static” model using column water vapor

“…Due to the complex meteorology of the San Joaquin flows and uncertainties surrounding the sources of ammonia, nitrogen oxides, and residential-burning smoke, we attempt to separate out some certain aspects of complex 3-D sourcedriven modeling (Bey et al, 2001;Nolte, 2015;Appel et al, 2017;Friberg et al, 2018) with a "static model" which does not attempt to simulate transport but rather uses observational records related to vertical mixing and AOT. The spatial maps produced can give a more detailed check on the 3-D process modeling.…”

“…We emphasize this and further extension the interpretation of satellite radiances, attempting to remain close to physical interpretations by using both multi-angle implementation of atmospheric correction (MAIAC) AOT and column water vapor (CWV) retrievals. MAIAC CWV (Lyapustin et al, 2018) retrievals have been quite acceptability validated with the AErosol RObotic NETwork (AERONET) CWV measurements in higher CWV environments (Martins et al, 2017(Martins et al, , 2018. It has not been previously recognized as a tool for improving ground PM estimation and, in particular, in the SJV.…”