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 observations.

对云量和大气成分的定量评估提高了我们利用气候反馈进入亚马逊流域的能力。在21世纪，亚马孙地区已经发生了3次干旱（例如2005年，2010年，2015年），导致大气成分的季节性格局发生了区域性变化。除气候外，大气动力和衰减特性是对该生态系统进行卫星遥感的长期挑战：高云度，丰富的水蒸气含量和生物质燃烧季节。因此，尽管气候分析支持对大气变化和趋势的理解，但它也为遥感应用提供了宝贵的见识。在这项研究中，我们评估了云量和大气成分（气溶胶含量，水汽和臭氧含量），重点放在气候分析和遥感方面。我们利用为中等分辨率成像光谱仪（MODIS）数据开发的多角度大气校正实施（MAIAC）算法获得的分辨率为1 km的新大气日用品的优势。气溶胶机器人网络（AERONET）与MAIAC气溶胶光学深度（AOD）和柱状水蒸气（CWV）的比对显示定量信息，且相关系数高于0.81。我们的结果表明，整个亚马逊河流域的云量分布存在明显的区域性格局：西北地区全年预设定了持续的云量（> 80％），而亚马逊南部在干旱季节则出现了低云量（0–20％）。在亚马逊南部的无云时期之后，由于火灾的排放，大气负担增加了。我们的结果表明，AOD记录的面积和强度都在变化。在2005年和2010年的干旱期间，SON季节总流域的AOD异常（δ> 0.1）分别超过总流域的39.03％（2.403亿公顷）和27.14％（1.6599亿公顷）。相反，最近的2015年干旱发生在年底（10月至12月），观察到这些异常率超过23.72％（1.45亿公顷），影响了亚马逊中部和东部地区-与之前的干旱不同。水蒸气具有较高的浓度值（4.0–5.0 g cm 在2005年和2010年的干旱期间，SON季节总流域的AOD异常（δ> 0.1）分别超过总流域的39.03％（2.403亿公顷）和27.14％（1.6599亿公顷）。相反，最近的2015年干旱发生在年底（10月至12月），观察到这些异常率超过23.72％（1.45亿公顷），影响了亚马逊中部和东部地区-与之前的干旱不同。水蒸气具有较高的浓度值（4.0–5.0 g cm 在2005年和2010年的干旱期间，SON季节总流域的AOD异常（δ> 0.1）分别超过总流域的39.03％（2.403亿公顷）和27.14％（1.6599亿公顷）。相反，最近的2015年干旱发生在年底（10月至12月），观察到这些异常率超过23.72％（1.45亿公顷），影响了亚马逊中部和东部地区-与之前的干旱不同。水蒸气具有较高的浓度值（4.0–5.0 g cm 与以前的干旱不同，有72％（1.45亿公顷）的土地影响了亚马逊中部和东部地区。水蒸气具有较高的浓度值（4.0–5.0 g cm 与以前的干旱不同，有72％（1.45亿公顷）的土地影响了亚马逊中部和东部地区。水蒸气具有较高的浓度值（4.0–5.0 g cm^-2）在雨季（DJF），而我们在干旱季节从盆地西北向东南观察到强烈的空间梯度。此外，我们还发现2000年至2015年之间的水蒸气含量（〜0.3 g / cm ²）呈正趋势。总臭氧量通常在220至270 DU之间变化，并且从2004年起，季节变化为〜25–35 DU。臭氧前体的大量排放和远距离运输造成的雨季至旱季。最后，尽管这项研究有助于对大气成分进行气候分析，但遥感用户还可以了解由大气衰减引起的区域限制，例如高气溶胶负荷和用于地面观测的云层障碍。