A Dark Target Method for Himawari-8/AHI Aerosol Retrieval: Application and Validation

Ge, Bangyu; Li, Zhengqiang; Liu, Li; Yang, Leiku; Chen, Xingfeng; Hou, Weizhen; Zhang, Yang; Li, Donghui; Li, Li; Qie, Lili

doi:10.1109/tgrs.2018.2854743

Cited by 47 publications

(23 citation statements)

References 60 publications

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“…Satellite remote sensing technology has the advantages of a large area coverage, a long effective time, and a low relative cost, and it has become one of the main methods used to obtain aerosol distribution information at a global scale [8]. A number of aerosol retrieval algorithms have been proposed and improved based on different satellite multi-channel sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [9][10][11], the Advanced Very High Resolution Radiometer [12], the Ozone Monitoring Instrument [13], and the Advanced Himawari Imager [14,15]. The MODIS sensors onboard the Terra and Aqua satellites of the Earth Observation System have a swath width of 2000 km, covering the entire globe nearly daily.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Jin

Zhang

et al. 2019

Remote Sensing

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Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products are used worldwide for their reliable accuracy. However, the aerosol optical depth (AOD) usually retrieved by the operational dark target (DT) algorithm of MODIS has been missing for most of the urban regions in Central China. This was due to a high surface reflectance and heavy aerosol loading, especially in winter, when a high cloud cover fraction and the frequent occurrence of haze events reduce the number of effective satellite observations. The retrieval of the AOD from limited satellite data is much needed and important for further aerosol investigations. In this paper, we propose an improved AOD retrieval method for 500 m MODIS data, which is based on an extended surface reflectance estimation scheme and dynamic aerosol models derived from ground-based sun-photometric observations. This improved method was applied to retrieve AOD during heavy aerosol loading and effectively complements the scarcity of AOD in correspondence with urban surface of a higher spatial resolution. The validation results showed that the retrieved AOD was consistent with MODIS DT AOD (R = ~0.87; RMSE = ~0.11) and ground measurements (R = ~0.89; RMSE = ~0.15) from both the Terra and the Aqua satellite. The method can be easily applied to different urban environments affected by air pollution and contributes to the research on aerosol.

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Section: Introductionmentioning

confidence: 99%

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Jin

Zhang

et al. 2019

Remote Sensing

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“…2g-i (third row) present the AOD mean percentage error of three AHI datasets over different land regions. Significant positive biases and negative biases of AHI AOD are still noticed over Australia and Southeast Asia in most of the AERONET stations respectively, which have been found in the previous AHI L2 aerosol products [31][32][33] and the validation results of AHI L3 aerosol products 37 . Comparatively, the AHI AOD performs better over eastern China, Korean Peninsula and Japan with a relatively lower uncertainty.…”

Section: Resultsmentioning

confidence: 51%

“…In addition, the coast AE merged retrievals present a relatively smaller bias than the land AE merged (bias = − 0.253 vs. bias = − 0.865). Overall, the poor performance of AHI L2 AE retrievals [31][32][33] continues to be noted in the L3 hourly products. In AHI L3 hourly combined algorithm, the AE merged product was obtained from AE pure retrievals by the same optimal interpolation method as AOD merged and can be calculated as follows 29,30 : www.nature.com/scientificreports/…”

Section: Resultsmentioning

confidence: 92%

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Comparison of hourly aerosol retrievals from JAXA Himawari/AHI in version 3.0 and a simple customized method

Wang

Chen

2020

Sci Rep

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Advanced Himawari imager (AHI) carried on the new-generation geostationary meteorological Himawari-8 satellite of Japan has been generating aerosol observations with a high temporal resolution since 7 July 2015. However, the previous studies lack a comprehensive quality assessment and spatial coverage analysis of AHI hourly aerosol products (level 3 version 3.0) across the full disk scan. The monitoring accuracy of different AHI aerosol products (AODpure and AODmerged) and a simple customized product (AODmean) was evaluated against Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) observations from May 2016 to February 2019 in this study. Results showed that AHI AODmean demonstrates a better agreement to AERONET AOD measurements than AODpure and AODmerged over land (R = 0.81, bias = − 0.011) and all the AHI land retrievals present a significant regional performance differences, while the relatively better performance is observed in AODmerged over the coastal regions (R = 0.89, bias = 0.053). Over ocean, AHI exhibited overall overestimation in retrieving AOD against MAN observations and the relatively lower uncertainties were found in AODpure retrievals (R = 0.96, bias = 0.057). The hourly comparisons in different AHI products demonstrated a robust performance in the late afternoon (16:00–17:00 LT) over land and around the noon (10:00–13:00 LT) over coast. AHI AOD products indicated an obvious underestimation when compared to MODIS AOD retrievals over both land and ocean. Furthermore, the performance differences of AHI AOD products have also affected by the vegetation cover, pollution levels and relative humidity. For spatiotemporal coverage, the results of different AHI products demonstrated that AODmean can achieve relatively higher coverage than AODpure and AODmerged, and AHI retrievals present significant regional differences in coverage capability.

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“…On the contrary, aerosol from satellite remote sensing observations has superiority in wide spatial coverage, however, how to decouple atmospheric and surface contributions from reflectance at the top of atmosphere is still challenging. To solve this problem, there are many algorithms have been proposed (Ge et al, 2019;Hou et al, 2018;Li et al, 2018;Qie et al, 2015;Wang et al, 2014a;Wang et al, 2014b;Wang et al, 2014c;Wang et al, 2014d;Waquet et al, 2014;Yang et al, 2014;Zhang et al, 2017;.…”

Section: Introductionmentioning

confidence: 99%

Validation and Comparison of Fine-Mode Aerosol Optical Depth Products Between Modis and Polder

Hou

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Fine-mode aerosol usually comes from anthropogenic emissions. The fine-mode aerosol optical depth (AODf) is an important parameter for estimating the particulate matter with an aerodynamic diameter little than 2.5 μm (PM2.5). Compared to the ground-based observations, AODf products from satellite remote sensing have an advantage of high spatial coverage, which is suitable for monitoring the air quality at a regional or global scale. Up to now, AODf products have been released by several sensors, such as the single-angle multi-spectral intensity sensor MODIS and multi-angle multi-spectral polarization sensor POLDER, then what’re the different performances of AODf products from them? In this study, the different spatial resolution AODf products respectively from MODIS latest Collection 6.1 (C6.1, 3 and 10 km) and POLDER latest level 2 version 1.01 (L2, 18 km) were firstly compared with each other in Beijing-Tianjin-Hebei (BTH) domains. Then those products were validated against the ground-based AERosol RObotic NETwork (AERONET) measurements, where has been suffering the severe air pollution since decades ago. The comparison of yearly averaged AODf products between MODIS and POLDER shows a good consistency on the spatial distribution, the higher spatial resolution products of MODIS show more details, both low values of AODf appeared in the northwest area with small population and industry, high values appeared in the southeast area with lots of cities, industries, and large population. However, the whole yearly AODf average values of MODIS are higher than that of POLDER. The results of validation against AERONET show that the accuracy of AODf products at 865 nm from POLDER (R = 0.94, RMSE = 0.05) is high than that at 550 nm of MODIS (3 km: R = 0.69, RMSE = 0.32; 10 km: R = 0.76, RMSE = 0.3). In this study, the performance of different spatial resolutions AODf products retrieved from the intensity (MODIS 3 and 10 km) and polarized sensors (POLDER 18 km) were evaluated. Those results not only have a great significance to provide users amore appropriate choice of the AODf products in the BTH region but also display that the accuracy and spatial resolution of MODIS and POLDER AODf products need to be improved.

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A Dark Target Method for Himawari-8/AHI Aerosol Retrieval: Application and Validation

Cited by 47 publications

References 60 publications

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Comparison of hourly aerosol retrievals from JAXA Himawari/AHI in version 3.0 and a simple customized method

Validation and Comparison of Fine-Mode Aerosol Optical Depth Products Between Modis and Polder

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