Abstract
Abstract. This study presents and evaluates several candidate approaches for
downscaling observations from the Spinning Enhanced Visible and
Infrared Imager (SEVIRI) in order to increase the horizontal
resolution of subsequent cloud optical thickness (τ) and
effective droplet radius (reff) retrievals from the
native ≈3km×3km spatial resolution of the
narrowband channels to ≈1km×1km. These methods make
use of SEVIRI's coincident broadband
high-resolution visible (HRV) channel. For four example cloud fields,
the reliability of each downscaling algorithm is evaluated by means of
collocated 1 km×1 km MODIS radiances, which are
reprojected to the horizontal grid of the HRV channel and serve as
reference for the evaluation. By using these radiances, smoothed with the
modulation transfer function of the native SEVIRI channels, as retrieval
input, the accuracy at the SEVIRI standard resolution can be evaluated
and an objective comparison of the accuracy of the different
downscaling algorithms can be made. For the example scenes considered
in this study, it is shown that neglecting high-frequency
variations below the SEVIRI standard resolution results in significant
random absolute deviations of the retrieved τ and
reff of up to ≈14 and
≈6 µm, respectively, as well as biases. By error propagation, this
also negatively impacts the reliability of the subsequent calculation
of liquid water path (WL) and cloud droplet number
concentration (ND), which exhibit deviations of up to
≈89gm-2 and ≈177cm-3, respectively. For τ, these deviations can be almost
completely mitigated by the use of the HRV channel as a physical constraint
and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from
SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals.
Reference49 articles.
1. Ardanuy, P. A., Han, D., and Salomonson, V. V.: The Moderate Resolution Imaging
Spectrometer (MODIS), IEEE T. Geosci. Remote, 30, 2–27, 1992. a
2. Barker, H. and Liu, D.: Inferring optical depth of broken clouds from Landsat
data, J. Climate, 8, 2620–2630, 1995. a
3. Barnes, W. L., Pagano, T. S., and Salomonson, V. V.: Prelaunch characteristics
of the 'Moderate Resolution Imaging Spectroradiometer' (MODIS) on EOS–AM1,
IEEE T. Geosci. Remote, 36, 1088–1100, 1998. a
4. Benas, N., Finkensieper, S., Stengel, M., van Zadelhoff, G.-J., Hanschmann, T., Hollmann, R., and Meirink, J. F.: The MSG-SEVIRI-based cloud property data record CLAAS-2, Earth Syst. Sci. Data, 9, 415–434, https://doi.org/10.5194/essd-9-415-2017, 2017. a
5. Benestad, R. E.: Empirical-statistical downscaling in climate modeling, Eos
Trans., 85, 417–422, https://doi.org/10.1029/2004EO420002, 2011. a
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