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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
04 Jan 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Quantifying and correcting the effect of vertical penetration assumptions on droplet concentration retrievals from passive satellite instruments
Daniel P. Grosvenor1, Odran Sourdeval2, and Robert Wood3 1School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
2Leipzig Institute for Meteorology, Universität Leipzig, Germany
3Department of Atmospheric Sciences, University of Washington, Seattle, USA
Abstract. Droplet concentration (Nd) retrievals from passive satellite retrievals of cloud optical depth (τ) and effective radius (re) usually assume the model of an idealised cloud in which the liquid water content (LWC) increases linearly between cloud base and cloud top (i.e., at a fixed fraction of the adiabatic LWC) with a constant Nd profile. Generally it is assumed that the retrieved re value is that at the top of the cloud. In reality, barring re retrieval biases due to cloud heterogeneity, etc., the retrieved re is representative of that lower down in the cloud due to the vertical penetration of photons at the shortwave infra-red wavelengths used to retrieve re. This inconsistency will cause an overestimate of Nd (referred to here as the penetration depth bias), which this paper quantifies. Here we estimate penetration depths in terms of optical depth below cloud top () for a range of idealised modelled adiabatic clouds using bispectral retrievals and plane-parallel radiative transfer. We find a tight relationship between and τ and that a 1-D relationship approximates the modelled data well. Using this relationship we find that values and hence Nd biases are higher for the 2.1 μm channel re retrieval (re2.1) compared to the 3.7 μm one (re3.7). The theoretical bias in the retrieved Nd is likely to be very large for optically thin clouds, nominally approaching infinity for clouds whose τ is close to the penetration depth. The relative Nd bias rapidly reduces as cloud thickness increases, although still remains above 20 % for τ < 19.8 and τ < 7.7 for re2.1 and re3.7, respectively.

The magnitude of the Nd bias upon climatological Nd data sets is estimated globally using one year of daily MODIS (MODerate Imaging Spectroradiometer) data. Screening criteria are applied that are consistent with those required to help ensure accurate Nd retrievals. The results show that the SE Atlantic, SE Pacific (where the VOCALS field campaign took place) and Californian stratocumulus regions produce fairly large overestimates due to the penetration depth bias with mean biases of 35–38 % for re2.1 and 17–20 % for re3.7. For the other stratocumulus regions examined the errors are smaller (25–30 % for re2.1 and 11–14 % for re3.7). Significant time variability in the percentage errors is also found with regional mean standard deviations of 20–40 % of the regional mean percentage error for re2.1 and 40–60 % for re3.7. This shows that it is important to apply a daily correction to Nd for the penetration depth error rather than a time-mean correction when examining daily data. We also examine the seasonal variation of the bias and find that the biases in the SE Atlantic, SE Pacific and Californian stratocumulus regions exhibit the most seasonality with the largest errors occurring in the December, January, February (DJF) season.

We show that this effect can be corrected for by simply removing from the observed τ and provide a function to allow the calculation of from τ. However, in reality this error will be combined with a number of other errors that affect both the re and τ, which are potentially larger and may compensate or enhance the bias due to vertical penetration depth.

Citation: Grosvenor, D. P., Sourdeval, O., and Wood, R.: Quantifying and correcting the effect of vertical penetration assumptions on droplet concentration retrievals from passive satellite instruments, Atmos. Meas. Tech. Discuss.,, in review, 2018.
Daniel P. Grosvenor et al.
Daniel P. Grosvenor et al.
Daniel P. Grosvenor et al.


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Short summary
We identify an error in retrievals of cloud droplet concentrations from satellite instruments due to the assumption that the retrieved cloud droplet size is representative of that at the top of the cloud, whereas in reality it is representative of that lower down. We show that the representative level within the cloud can be characterized as a function of optical depth only, allowing the quantification of the amount of error (up to +38% for stratocumulus) and a correction to be made.
We identify an error in retrievals of cloud droplet concentrations from satellite instruments...