Changes in Aerosol Optical Depth over the Arctic Ocean as Seen by CALIOP, MAIAC, and MODIS C6.1

Due to the recent increase in Arctic shipping, 2006-2020 June to October Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1), and Multi-Angle Implementation of Atmospheric Correction (MAIAC) retrieved aerosol optical depth (AOD) data were examined for changes in AOD from period 1 (P1, 2006-2012) to period 2 (P2, 2014-2020 (P2). Herein, AOD was statistically analyzed on a 0.25° × 0.25° grid and in the airsheds over the various ocean basins over the Arctic north of 59.75°N. According to heatmaps of the correlation between AOD and ship traffic, and AOD and fire emissions for the airsheds, all three AOD products captured the observed inter-annual variability in wildfire occurrence well, and showed wildfire emissions over Siberia were more severe in P2 than P1. Except for the Atlantic, North, and Baltic Seas, Beaufort Sea, and Barents Sea, all three AOD products indicated that AOD was higher over the various basins in P2 than P1, but disagreed on the magnitude. This fact suggests that the detection of changes in the typical low AOD over the Arctic Ocean might be rather qualitative than quantitative. While all products captured increases in AOD due to ships at berth, only MODIS C6.1 caught the elevated AOD due to shipping on the Siberian rivers. Obviously, sub-daily resolutions are required to capture increased AOD due to short-term events like a traveling ship or short-interval fire.

Using MAN and Coastal AERONET Measurements to Assess the Suitability of MODIS C6.1 Aerosol Optical Depth for Monitoring Changes from Increased Arctic Shipping

Collocated data of the moderate resolution imaging spectroradiometer (MO-DIS) Collection 6.1 aerosol optical depths (AOD) at 3 km × 3 km north of 59.9°N over ocean were assessed at 550 nm by aerosol robotic network (AERONET) data from coastal sites and marine aerosol network (MAN) data from vessels during June to October 2006 to 2018. Typically, MODIS AOD was higher at low and lower at high values than the AERONET AOD. Discrepancies were largest for sites where the Earth’s surface around the site is very heterogeneous (Canadian Archipelago, coast of Greenland). Due to the higher likelihood for sea-ice, MAN and MODIS AOD differed stronger west of Greenland and over the Beaufort Sea than at location in the Greenland and Norwegian Seas and Atlantic. MODIS AOD well captured the inter-seasonal variability found in the AERONET AOD data (R = 0.933). At all sites, MO-DIS and AERONET AOD agreement improved as time progressed in the shipping season, hinting at errors in sea-ice vs. open water classification. Overall 75.3% of the MODIS AOD data fell within the limits of the error envelops of the AERONET/MAN AOD data with MAN ranging between 87.5% and 100%. Changes in both MODIS and AERONET mean AOD between two periods of same length (2006-2011, 2013-2018) were explainable by changes in emissions for all sites.

Spike in phytoplankton biomass in Greenland Sea during 2009 and the correlations among chlorophyll-a,aerosol optical depth and ice cover

The distributions and correlations of chlorophyll-a(Chl-a),aerosol optical depth(AOD)and ice cover in the southeast Arctic Ocean-Greenland Sea(10°W–10°E,70°–80°N)between 2003 and 2009 were studied using satellite data and statistical analyses.Regression analysis showed correlations between Chl-a and AOD,Chl-a and ice cover,and AOD and ice cover with different time lags.The time lag of Chl-a and AOD indicated their long-term equilibrium relationship.Peaks in AOD and Chl-a and generally occurred in May and July,respectively.Despite the time lag,the correlation between Chl-a and AOD in the study region was as high as 0.7.The peak gap between Chl-a and AOD shifted for about 6 weeks during 2003–2009.In the summer and autumn of 2009,Chl-a and AOD levels were much higher than during the other years,especially in the northern band of the study region(75°–80°N).The driving forces for this localized increase in phytoplankton biomass could be mainly attributed to the very high rate of ice melting in spring and early summer and the high wind speed in autumn,together with the increased deposition of aerosol throughout the year.The unusually high AOD in the spring of 2003 was mainly due to a massive fi re in Russia,which occurred in the fi rst half of the year.Over the 7 years of the study,the sea surface temperature generally decreased.This may have been due to the release of dimethylsulfi de into the air,excreted in large amounts from abundant phytoplankton biomass,and its subsequent reaction,form large amounts of aerosol,and resulting in regional cooling.

Importance of Aerosol Optical Depth in the Atmospheric Correction of Ocean Colour Remote Sensing Data

Atmospheric aerosols being an important component of the atmosphere play an important role in global and regional climate change. Aerosols can affect air quality, climate change and human health and have a significant effect on the solar energy budget. To study their quantitative effect is a challenging task due to their high spatial and temporal variability. This parameter represents one of the extinction coefficients of solar radiation and rate of suspended particles in the atmosphere. Ocean Colour Remote Sensing provides information about the four major geophysical parameters like chlorophyll and total suspended sediment concentration, vertical diffuse attenuation co-efficient and the aerosol optical thickness measured at 865 nm. Aerosol optical depth can be expressed as function of wavelength through Angstrom’s equation ?, where “α” and “β” are known as Angstrom parameters. The Angstrom exponent, “α” is related to the size distribution of the aerosol particles and “β” represents the amount of aerosols present in the atmosphere. In this present study, an attempt is made to study the impact of these two parameters by changing values from 0 to 0.05 for “α” and from 0.0 to 0.6 for “β” in SeaDAS processing for estimating the aerosol optical depth. From this study, it is clear that for most of the applications either in the coastal or open ocean waters, alpha value varies from 0.0 to 0.3 over the north Indian Ocean. However, this has been further evaluated by various combinations for retrieving the AOD using OCM-2 data.

基于MODIS和CALIOP卫星遥感数据的气溶胶光学厚度与海洋初级生产力相关性

利用2003~2014年的MODIS和2009~2014年的CALIOP卫星遥感数据产品,分析了我国华北地区(32°N^42°N,112°E^121°E)气溶胶光学厚度和西北太平洋部分海域(40°N^50°N,150°E^180°E)海洋初级生产力的时空分布,并研究了二者之间的相关性.结果表明:我国华北地区气溶胶光学厚度具有年季周期性,在每年的6、7月达到峰值;西北太平洋初级生产力同样具有年季周期性,在每年的8、9月达到峰值;从华北地区到西北太平洋,在5、6月可以发现比较明显的气溶胶传输通道,高空风场也与之对应;通过对长时间序列数据进行时滞相关性分析,发现华北地区气溶胶光学厚度与滞后其1~2个月的西北太平洋初级生产力有较高相关性,相关系数在0.7-0.8(通过a=0.05的显著性检验)之间.但其中存在滞后时间短相关系数低的海域,可能是受到洋流输送的影响.

中国东部地区气溶胶光学特性和类型特性分析

本文基于我国东部沿海岸线分布的Beijing-RADI、Beijing-CAMS、Xuzhou-CUMT、Taihu、Hong_Kong_PolyU、Hong_Kong_Sheung六个AERONET长期观测站点的光学厚度(AOD)、Angstrom指数(AE)、单次散射反照率(SSA)、细粒子百分比(FMF)四种气溶胶的物理光学特性观测产品,结合Terra/Aqua MODIS Level2 C6 AOD产品,研究了我国东部地区气溶胶时空变化特性及类型特性。研究表明:1)北京、徐州、太湖、香港地区四个地区地基的AOD年均值徐州>太湖>北京>香港地区,依次为0.805±0.129、0.775±0.069、0.664±0.197、0.519±0.125;2)在AERONET站点处,MODIS AOD年均值检测值太湖>徐州>香港地区>北京,依次为0.902±0.227、0.772±0.082、0.547±0.064、0.517±0.234,与地基检测值依次相差22.2%、4.1%、5.5%、16.3%;3)AE年均值香港地区>太湖>徐州>北京,依次为1.314±0.054、1.213±0.084、1.198±0.104、1.118±0.078,表明中国东部地区污染物的粒径从北往南逐渐减小;4)北京、徐州、太湖、香港地区四个地区均以弱吸收型细粒子所占比重最大,依次为38.29%、44.99%、44.30%、48.14%,中度吸收型细粒子和强散射细粒子次之,其他类型的粒子均较少。

MODIS遥感中国东部海域气溶胶光学厚度与现场测量数据的对比分析

利用2006年4月至2007年11月间中国东部海域五个航次的天空辐射计海上观测资料,以10 km×10 km和±1 h作为时空匹配窗口,对中分辨率成像光谱仪(MODIS)标准海色产品中的869 nm气溶胶光学厚度数据进行了对比检验。结果显示,在全部匹配数据中,72%非常接近或在NASA公布的期望误差Δτ=±0.03±0.05τ范围以内。MODIS的反演精度具有一定的地域性和季节性差异,东海匹配数据的一致性明显好于黄海,2006年冬季匹配数据的一致性较好,2007年秋季MODIS反演值存在系统性偏高的情况,其主要原因可能与气溶胶模型的不适用有关。通过对全部匹配数据的进一步分析印证了这一点。

基于静止卫星GOCI数据的陆地上空气溶胶光学厚度遥感反演

以长江三角洲地区为研究区,基于2013年共72d的晴空GOCI数据,利用深蓝算法进行了研究区上空气溶胶光学厚度的遥感反演研究,并利用两个实测站点数据进行了验证。结果表明:GOCI数据可以用于陆地气溶胶的反演,两个站点均呈现较高的拟合精度,南京信息工程大学北辰楼站拟合度为0.659,AERONET太湖站拟合度为0.747,与MODIS气溶胶产品相比也表现出很好的一致性。同时,研究发现基于静止卫星GOCI数据的气溶胶产品具有监测气溶胶日内变化的能力,为气溶胶的动态扩散和气候效应研究等提供参考和借鉴。