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.

Spatio-Temporal Variations in the Associations between Hourly PM_2.5and Aerosol Optical Depth (AOD) from MODIS Sensors on Terra and Aqua

Recent studies have explored the relationship between aerosol optical depth (AOD) measurements by satellite sensors and concentrations of particulate matter with aerodynamic diameters less than 2.5 μm (PM2.5). However, relatively little is known about spatial and temporal patterns in this relationship across the contiguous United States. In this study, we investigated the relationship between US Environmental Protection Agency estimates of PM2.5 concentrations and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD measurements provided by two NASA satellites (Terra and Aqua) across the contiguous United States during 2005. We found that the combined use of both satellite sensors provided more AOD coverage than the use of either satellite sensor alone, that the correlation between AOD measurements and PM2.5 concentrations varied substantially by geographic location, and that this correlation was stronger in the summer and fall than that in the winter and spring.

Applications of Satellite Data for Aerosol Optical Depth (AOD) Retrievals and Validation with AERONET Data

An understanding of the amount and type of aerosols present in the atmosphere is required for the atmospheric correction of satellite imagery. A sensitivity analysis of the atmospheric inputs to the MOD09 software has shown that uncertainty in the estimation of Aerosol Optical Depth (AOD) has the greatest impact on the accuracy of atmospheric correction of MODIS data. The MOD09 software used for the generation of surface reflectance products estimates the AOD of the atmosphere at the time of image acquisition. AOD measurements retrieved from MODIS were compared with near-simultaneous AErosol RObotic NETwork (AERONET) data over three sites in Australia, using time-series of MODIS surface reflectance products. The results of the study provide an important independent validation of ACRES MODIS Surface Reflectance Products. This procedure may be applied to long time series MODIS data for estimating the accuracy of MOD09 retrieved AOD.

葵花-8卫星AOD资料在CMA-MESO/CUACE CW 3DVar同化系统中的个例应用研究

CMA-MESO/CUACE CW化学天气耦合模式是自主研发的大气化学耦合模式,目前CMA-MESO/CUACE CW3DVar同化系统实现了地面气溶胶观测可吸入颗粒物PM_(2.5)和PM10的同化,为增强耦合同化系统非常规观测的同化能力,文中在CMA-MESO大气化学天气耦合三维变分同化框架基础上,利用查表法获得气溶胶消光系数,然后建立气溶胶光学厚度(AerosolOpticalDepth,AOD)和气溶胶组分之间关系的观测算子、切线性观测算子和伴随观测算子,实现AOD观测资料的同化应用。针对2016年12月18-20日华北、黄淮地区一次污染天气过程进行同化预报试验,试验结果表明同化葵花-8卫星(Hi‐mawari-8)气溶胶光学厚度观测后,PM_(2.5)分析的重污染区范围有所扩大,山西东南部分析与实况分布更为接近,但是山东大部地区PM_(2.5)分析偏强,与观测相比PM_(2.5)质量浓度存在高估。同时同化Himawari-8 AOD观测和地面气溶胶站点观测的PM_(2.5)分析最优,分析与观测距平相关系数最高,平均偏差、均方根误差及标准差最小。重污染区的PM_(2.5)预报检验结果表明,同化Himawari-8AOD观测对大于350µg·m^(-3)量级PM_(2.5)预报正贡献可以持续到48 h,但整体来说,同时同化Himawari-8AOD观测和地面气溶胶站点观测对各个量级的PM_(2.5)质量浓度预报质量最优。

A Method for Spaceborne Synthetic Remote Sensing of Atmospheric Aerosol Optical Depth and Vegetation Reflectance

Spaceborne synthetic remote sensing of atmospheric aerosol optical depth and vegetation reflectance is very significant, but it remains to be a question unresolved yet. Based on the property of vegetation reflectance spectra from near ultra violet to near infrared and the sensitivity of outgoing radiance to vegetation reflectance and atmospheric aerosol optical depth, a new method for spaceborne synthetic remote sensing of the reflectance and the depth is proposed, and an iteration correlation inversion algorithm is developed in this paper. According to numerical experiment, effects of radiance error, error in aerosol imaginary index and vegetation medium inhomogeneity on retrieved result are analyzed. Inversion results show that the effect of error in aerosol imaginary index is very important. As the error of aerosol imaginary index is within 0.01, standard errors of aerosol optical depth and vegetation reflectance solutions for 14 spectral channels from 410 nm to 900 nm are respectively less than 0.063 and 0.023. And as the radiance error is within 2%, the standard errors are less than 0.023 and 0.0056.

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.

Determining the environmental and atmospheric effects of coronavirus disease 2019(COVID-19)quarantining by studying the total aerosol optical depth,black carbon,organic matter,and sulfate in Blida City of Algeria

Background:To study,estimate and discuss the variations of the aerosol optical depth(AOD),black carbon,sulfate and organic matter,in the atmosphere in Blida City of Algeria,which was greatly affected by COVID-19 pandemic.Methods:We analyzed the effects of changes in the total AOD,black carbon,sulfate,and organic matter in the atmosphere(λ=550 nm)in the same period of 2019 and 2020,following the COVID-19 epidemic in Blida City,which was the most-affected city in Algeria.Results:The quarantine that was enacted to limit the spread of COVID-19 resulted in side effects that were identifiable in the total AOD and in some of its atmospheric components.Comparing these variables in 2019 and 2020(in the months during the quarantine)revealed that in April,the BCAOD values were much lower in 2020than in 2019.Conclusion:Based on the effects of the emerging COVID-19,the research listed the changes received from the AOD,and is considered as a comparative study and represents a significant side effect of the quarantine that was mainly designed to limit COVID-19.

The relationships among aerosol optical depth, ice, phytoplankton and dimethylsulfide and the implication for future climate in the Greenland Sea

The sea-to-air flux of dimethylsulphide（DMS） is one of the major sources of marine biogenic aerosol, and can have an important radiative impact on climate, especially in the Arctic Ocean. Satellite-derived aerosol optical depth（AOD） is used as a proxy for aerosol burden which is dominated by biogenic aerosol during summer and autumn. The spring sea ice melt period is a strong source of aerosol precursors in the Arctic. However, high aerosol levels in early spring are likely related to advection of continental pollution from the south（Arctic haze）.Higher AOD was generally registered in the southern part of the study region. Sea ice concentration（SIC） and AOD were positively correlated, while cloud cover（CLD） and AOD were negative correlation. The seasonal peaks of SIC and CLD were both one month ahead of the peak in AOD. There is a strong positive correlation between AOD and SIC. Melting ice is positively correlated with chlorophyll a（CHL） almost through March to September,but negatively correlated with AOD in spring and early summer. Elevated spring and early summer AOD most likely were influenced by combination of melting ice and higher spring wind in the region. The peak of DMS flux occurred in spring due to the elevated spring wind and more melting ice. DMS concentration and AOD were positively correlated with melting ice from March to May. Elevated AOD in early autumn was likely related to the emission of biogenic aerosols associated with phytoplankton synthesis of DMS. The DMS flux would increase more than triple by 2100 in the Greenland Sea. The significant increase of biogenic aerosols could offset the warming in the Greenland Sea.

Modeling Study of the Impact of Heterogeneous Reactions on Dust Surfaces on Aerosol Optical Depth and Direct Radiative Forcing over East Asia in Springtime

The spatial distributions and interannual variations of aerosol concentrations, aerosol optical depth （AOD）, aerosol direct radiative forcings, and their responses to heterogeneous reactions on dust surfaces over East Asia in March 2006-10 were investigated by utilizing a regional coupled climate-chemistry/aerosol model. Anthropogenic aerosol concentrations （inorganic ＋ carbonaceous） were higher in March 2006 and 2008, whereas soil dust reached its highest levels in March 2006 and 2010, resulting in stronger aerosol radiative forcings in these periods. The domain and five-year （2006-10） monthly mean concentrations of anthropogenic and dust aerosols, AOD, and radiative forcings at the surface （SURF） and at the top of the atmosphere （TOA） in March were 2.4 μg m 3 13.1 lag m^-3, 0.18, -19.0 W m^-2, and -7.4 W m^-2, respectively. Heterogeneous reactions led to an increase of total inorganic aerosol concentration; however, the ambient inorganic aerosol concentration decreased, resulting in a smaller AOD and weaker aerosol radiative forcings. In March 2006 and 2010, the changes in ambient inorganic aerosols, AOD, and aerosol radiative forcings were more evident. In terms of the domain and five-year averages, the total inorganic aerosol concentrations increased by 13.7% （0.17 μg m^-3） due to heterogeneous reactions, but the ambient inorganic aerosol concentrations were reduced by 10.5% （0.13 lag m-3）. As a result, the changes in AOD, SURF and TOA radiative forcings were estimated to be -3.9% （-0.007）, -1.7% （0.34 W m^-2）, and -4.3% （0.34 W m^-2）, respectively, in March over East Asia.

Investigating the Long-Term Relationship between Aerosol Optical Thickness and Land Use/Cover Change in Guangxi Coastal Cities, China

Land Use/Cover Change (LUCC) has an impact on AOD to a certain extent. It is of great significance for ecological environment and public health to pay attention to and explore the response mechanism of AOD to LUCC. Based on remote sensing satellite technology, using landsat8 and MODIS data, this paper analyzes the correlation between different land use types and AOD in Beibu Gulf coastal urban belt under the background of wide-scale region and long time series, and further discusses the difference value and contribution level of each LUCC to AOD. The results show that: 1) there is a positive correlation between PM concentration and cultivated land, urban land, water area and other types of land, and the correlation coefficient increases in turn, R is 0.812, 0.685, 0.627, 0.416, respectively, which indicates that the increase of cultivated land and urban land increases PM concentration to a certain extent;2) there is a significant negative correlation between PM concentration and forest land, R is -0.924, The results show that the decrease of woodland is an important factor for the increase of atmospheric particulate matter concentration in the study area from 2015 to 2019;3) through the contribution analysis method, the contribution of cultivated land to AOD is the largest, followed by urban land, and the water area is the smallest in 2015-2019, which indicates that the land use mode is closely related to AOD. It can be helpful to reasonably plan land use types and scientifically optimize land use structure. It can effectively reduce the concentration of air pollution particles.

A Deep-Learning and Transfer-Learning Hybrid Aerosol Retrieval Algorithm for FY4-AGRI:Development and Verification over Asia

The Advanced Geosynchronous Radiation Imager(AGRI)is a mission-critical instrument for the Fengyun series of satellites.AGRI acquires full-disk images every 15 min and views East Asia every 5 min through 14 spectral bands,enabling the detection of highly variable aerosol optical depth(AOD).Quantitative retrieval of AOD has hitherto been challenging,especially over land.In this study,an AOD retrieval algorithm is proposed that combines deep learning and transfer learning.The algorithm uses core concepts from both the Dark Target(DT)and Deep Blue(DB)algorithms to select features for the machinelearning(ML)algorithm,allowing for AOD retrieval at 550 nm over both dark and bright surfaces.The algorithm consists of two steps:①A baseline deep neural network(DNN)with skip connections is developed using 10 min Advanced Himawari Imager(AHI)AODs as the target variable,and②sunphotometer AODs from 89 ground-based stations are used to fine-tune the DNN parameters.Out-of-station validation shows that the retrieved AOD attains high accuracy,characterized by a coefficient of determination(R2)of 0.70,a mean bias error(MBE)of 0.03,and a percentage of data within the expected error(EE)of 70.7%.A sensitivity study reveals that the top-of-atmosphere reflectance at 650 and 470 nm,as well as the surface reflectance at 650 nm,are the two largest sources of uncertainty impacting the retrieval.In a case study of monitoring an extreme aerosol event,the AGRI AOD is found to be able to capture the detailed temporal evolution of the event.This work demonstrates the superiority of the transfer-learning technique in satellite AOD retrievals and the applicability of the retrieved AGRI AOD in monitoring extreme pollution events.

Can MODIS Detect Trends in Aerosol Optical Depth over Land?

The Moderate Resolution Imaging Spectroradiometer （MODIS） sensor onboard NASA＇s Aqua satellite has been collect- ing valuable data about the Earth system for more than 14 years, and one of the benefits of this is that it has made it possible to detect the long-term variation in aerosol loading across the globe. However, the long-term aerosol optical depth （AOD） trends derived from MODIS need careful validation and assessment, especially over land. Using AOD products with at least 70 months＇ worth of measurements collected during 2002-15 at 53 Aerosol Robotic Network （AERONET） sites over land, Mann-Kendall （MK） trends in AOD were derived and taken as the ground truth data for evaluating the corresponding results from MOD｜S onboard Aqua. The results showed that the AERONET AOD trends over all sites in Europe and North Amer- ica, as well as most sites in Africa and Asia, can be reproduced by MODIS/Aqua. However, disagreement in AOD trends between MODIS and AERONET was found at a few sites in Australia and South America. The AOD trends calculated from AERONET instantaneous data at the MODIS overpass times were consistent with those from AERONET daily data, which suggests that the AOD trends derived from satellite measurements of 1-2 overpasses may be representative of those from daily measurements.

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.

Simulating Aerosol Optical Depth and Direct Radiative Effects over the Tibetan Plateau with a High-Resolution CAS FGOALS-f3 Model

Current global climate models cannot resolve the complex topography over the Tibetan Plateau(TP)due to their coarse resolution.This study investigates the impacts of horizontal resolution on simulating aerosol and its direct radiative effect(DRE)over the TP by applying two horizontal resolutions of about 100 km and 25 km to the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere Land System(CAS FGOALS-f3)over a 10-year period.Compared to the AErosol RObotic NETwork observations,a high-resolution model(HRM)can better reproduce the spatial distribution and seasonal cycles of aerosol optical depth(AOD)compared to a low-resolution model(LRM).The HRM bias and RMSE of AOD decreased by 0.08 and 0.12,and the correlation coefficient increased by 0.22 compared to the LRM.An LRM is not sufficient to reproduce the aerosol variations associated with fine-scale topographic forcing,such as in the eastern marginal region of the TP.The difference between hydrophilic aerosols in an HRM and LRM is caused by the divergence of the simulated relative humidity(RH).More reasonable distributions and variations of RH are conducive to simulating hydrophilic aerosols.An increase of the 10-m wind speed in winter by an HRM leads to increased dust emissions.The simulated aerosol DREs at the top of the atmosphere(TOA)and at the surface by the HRM are–0.76 W m^(–2)and–8.72 W m^(–2)over the TP,respectively.Both resolution models can capture the key feature that dust TOA DRE transitions from positive in spring to negative in the other seasons.

Recent Trends in Satellite-Derived Chlorophyll and Aerosol Optical Depth Together with Simulated Dimethylsulfide in the Eastern China Marginal Seas

The biogenic compound dimethylsulfide(DMS)produced by a range of marine biota is the major natural source of re-duced sulfur to the atmosphere and plays a major role in the formation and evolution of aerosols,potentially affecting climate.The spatio-temporal distribution of satellite-derived chlorophyll_a(CHL)and aerosol optical depth(AOD)for the recent years(2011-2019)in the Eastern China Marginal Seas(ECMS)(25°-40°N,120°-130°E)are studied.The seasonal CHL peaks occurred during late April and the CHL distribution displays a clear zonal gradient.Elevated CHL was also observed along the northern and western coastlines during summer and winter seasons.Trend analysis shows that mean CHL decreases by about 10%over the 9-year study period,while AOD was higher in south and lower in north during summertime.A genetic algorithm technique is used to calibrate the key model parameters and simulations are carried out for 2015,a year when field data was available.Our simulation results show that DMS seawater concentration ranges from 1.56 to 5.88 nmol L^(−1) with a mean value of 2.76 nmol L^(−1).DMS sea-air flux ranges from 2.66 to 5.00mmol m^(−2) d^(−1) with mean of 3.80mmol m^(−2) d^(−1).Positive correlations of about 0.5 between CHL and AOD were found in the study region,with higher correlations along the coasts of Jiangsu and Zhejiang Provinces.The elevated CHL concentration along the west coast is correlated with increased sea-water concentrations of DMS in the region.Our results suggest a possible influ-ence of DMS-derived aerosol in the local ECMS atmosphere,especially along the western coastline of ECMS.

Study on Probability Distributions of Multi-Timescale Aerosol Optical Depth Using AERONET Data

The probability distribution analysis is per-formed for multi-timescale aerosol optical depth (AOD) using AErosol RObotic NETwork (AERONET) level 2.0 data.The maximum likelihood estimation is employed to determine the best-fit probability density function (PDF),and the statement that the fitting Weibull distribution will be light-tailed is proved true for these AOD samples.The best-fit PDF results for multi-site data show that the PDF of AOD samples with longer timescale in most sites tends to be stably represented by lognormal distribution,while Weibull distribution is a better fit for AOD samples with short timescales.The reason for this difference is ana-lyzed through tail characteristics of the two distributions,and an indicator for the selection between Weibull and lognormal distributions is suggested and validated.The result of this research is helpful for determining the most accurate AOD statistics for a given site and a given time-scale and for validating the retrieved AOD through its PDF.

Effect of model errors in ambient air humidity on the aerosol optical depth obtained via aerosol hygroscopicity in eastern China in the Atmospheric Chemistry and Climate Model Intercomparison Project datasets

This analysis of the multi-model aerosol optical depth (AOD) in eastern China using the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) datasets shows that the global models underestimate the AOD by 33% and 44% in southern and northern China, respectively, and decrease the relative humidity (RH) of the air in the surface layer to 71%–80%, which is less than the RH of 77%–92% in reanalysis meteorological datasets. This indicates that the low biases in the RH partially account for the errors in the AOD. The AOD is recalculated based on the model aerosol concentrations and the reanalysis humidity data. Improving the mean value of the RH increases the multi-model annual mean AOD by 45% in southern China and by 33% in June–August in northern China. This method of improving the AOD is successful in most of the ACCMIP models, but it is unlikely to be successful in GISS-E2-R, in which the plot of its AOD efficiency against RH strongly deviates from the rest of the models. The effect of the improvement in the modeled RH on the AOD depends on the concentration of aerosols. The shape error in the frequency distribution of the RH is likely to be more important than the error in the mean value of the RH, but this requires further research.

Assessment of Dust Aerosol Optical Depth and Shortwave Radiative Forcing over the Northwest Pacific Ocean in Spring Based on Satellite Observations

Dust aerosol optical depth (AOD) and its ac-companying shortwave radiative forcing (RF) are usually simulated by numerical models.Here,by using 9 months of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product data in combination with Clouds and the Earth's Radiant Energy System Single Scanner Footprint (CERES/SSF) data,dust AOD and its shortwave RF were estimated over the cloud-free north-west (NW) Pacific Ocean in the springs of 2004,2005,and 2006.The results showed that in this region,the mean dust AOD and its shortwave RF were 0.10 and 5.51 W m 2,respectively.In order to validate the dust AOD de-rived by MODIS,results from the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model were also used here.The correlation coefficient between the monthly averaged dust AOD derived by MODIS measurements and the model simulation results was approximately 0.53.Since the estimates of the dust AOD and its shortwave RF obtained in this study are based mainly on satellite data,they offer a good reference for numerical models.

Validation of Aerosol Optical Depth from Terra and Aqua MODIS Retrievals over a Tropical Coastal Site in China

This study compares the aerosol optical depth (AOD) Level 2 Collection 5 products from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) with ground-based measurements from a Microtops II sun photometer over Sanya (18.23°N,109.52°E),a tropical coastal site in China,from July 2005 to June 2006.The results indicate that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the measurements from the Microtops II sun photometer.The correlation coefficients for the linear regression fits (R2) are 0.83 for Terra and 0.78 for Aqua,and the regressed intercepts are near zero (0.005 for Terra,0.009 for Aqua).However,the Terra and Aqua MODIS are found to consistently underestimate AOD with respect to the Microtops II sun photometer,with slope values of 0.805 (Terra) and 0.767 (Aqua).The comparison of the monthly mean AOD indicates that for each month,the Terra and Aqua MODIS retrievals are matched with corresponding Microtops measurements but are systematically less than those of the Microtops.This validation study indicates that the Terra and Aqua MODIS AOD retrievals can adequately characterize the AOD distributions over the tropical coastal region of China,but further efforts to eliminate systematic errors are needed.

Trend Analysis of Aerosol Optical Depth and &#197ngstr&#246m Exponent Anomaly over East Africa

Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and &#197ngstr&#246m Exponent Anomaly (&#197EA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and &#197EA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and &#197EA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.