Abstract
Abstract. Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.
Highlights
The challenge of observing atmospheric processes over the Sahara desert remains a fundamental obstacle in our understanding of the climate system of Africa, a key region for diagnosing global radiation budgets (Allan et al, 2007), aerosol transport (Schepanski et al, 2009), Atlantic hurricane activity (Dunion and Velden, 2004), and climate change (Giorgi, 2006)
Across all 24 flights and using every valid data point, we find that 91 % ± 8 % of pixels where Spinning Enhanced Visible and InfraRed Imager (SEVIRI) did not detect a cloud in the AllCloud mask matched with an aircraft cloud fraction of less than 0.1, showing excellent agreement between the datasets for clear skies (Fig. 6a)
Derived products used to identify and characterise cloud over the Sahara desert based on the SEVIRI instrument aboard the Meteosat Second Generation (MSG) geostationary satellite have been compared to airborne cloud remote sensing products from the FAAM BAe146 aircraft during the Fennec Campaign. This provides the first evaluation of satellite cloud data using detailed observations in the extremely data-sparse region of the Sahara, which has an important impact on the global radiation budget
Summary
The challenge of observing atmospheric processes over the Sahara desert remains a fundamental obstacle in our understanding of the climate system of Africa, a key region for diagnosing global radiation budgets (Allan et al, 2007), aerosol transport (Schepanski et al, 2009), Atlantic hurricane activity (Dunion and Velden, 2004), and climate change (Giorgi, 2006) Much of this difficulty arises from a lack of in situ observational networks across vast expanses of uninhabited, inhospitable desert, leading to difficulties in the investigation of important climatological features such as the Saharan heat low (SHL; Lavaysse et al, 2009). Et al.: Performance of MSG cloud retrievals over the Sahara
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