Abstract

Abstract. To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

Highlights

  • To accurately predict future climate, it is essential to reduce the uncertainty in the representation of aerosols, clouds and their radiative impacts in climate models (Myhre et al, 2013)

  • The aerosol and cloud properties observed by SEVIRI are presented in Fig. 2 together with the MODIS products from the Terra overpasses at 10:00 UTC and 11:40 UTC

  • A very good spatial agreement is observed with the MOD06ACAERO product (Fig. 2d), but the values are slightly larger than the SEVIRI aerosol optical thickness (AOT)

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Summary

Introduction

To accurately predict future climate, it is essential to reduce the uncertainty in the representation of aerosols, clouds and their radiative impacts in climate models (Myhre et al, 2013). New in situ and remote sensing strategies are needed to improve our understanding of aerosol– cloud–radiation interactions and to constrain models (Seinfeld et al, 2016). The biomass burning aerosols emitted from July to October in southern Africa are mostly transported westward in the residual continental boundary layer in the free troposphere (Abel et al, 2020). These absorbing biomass burning particles are frequently observed above the extensive stratocumulus deck covering the SEAO. For this reason, the region has been the focus of much work over the past few years. In addition to improving our knowledge about aerosol– cloud–radiation interaction processes and constraining numerical weather forecast and climate models, this dataset provides, for the first time, direct observations of aerosol above clouds for validating emerging satellite retrievals

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