An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation

• Published in: Atmospheric Chemistry and Physics
• Main Authors: N. Schutgens, A. M. Sayer, A. Heckel, C. Hsu, H. Jethva, G. de Leeuw, P. J. T. Leonard, R. C. Levy, A. Lipponen, A. Lyapustin, P. North, T. Popp, C. Poulsen, V. Sawyer, L. Sogacheva, G. Thomas, O. Torres, Y. Wang, S. Kinne, M. Schulz, P. Stier
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: Physics; QC1-999; Chemistry; QD1-999; Aerosol Robotic Network
• Online Access: https://doi.org/10.5194/acp-20-12431-2020; https://doaj.org/article/0f8703ab6974454fb61b77f0d18f3d28

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="18e249d247dd6d35235fb683ecd82671"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12431-2020-ie00001.svg" width="34pt" height="11pt" src="acp-20-12431-2020-ie00001.png"/></svg:svg> daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" ...