Anisotropy of water cloud reflectance: A comparison of measurements and 1D theory

Horváth, Ákos; Davies, Roger

doi:10.1029/2003gl018386

Cited by 36 publications

(42 citation statements)

References 22 publications

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“…Similarly, Barker and Li (1997) reported significant deviations from 1-D radiative transfer due to horizontal photon transport if the horizontal dimensions of a considered atmospheric column are decreased. Horvath and Davies (2004) provided further evidence for the relevance of 3-D radiative effects through the observed anisotropy in the reflected solar radiation, which increasingly deviates from 1-D radiative transfer if the spatial resolution of the satellite is increased. Zinner and Mayer (2006) reported that at 1 km scale, the errors associated with horizontal photon transfer and the plane-parallel approximation cancel at least to some degree for stratiform boundary layer clouds.…”

Section: Spatial Representativeness Of a Point Measurementmentioning

confidence: 83%

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

et al. 2017

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Abstract. The time series of global radiation observed by a dense network of 99 autonomous pyranometers during the HOPE campaign around Jülich, Germany, are investigated with a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet. For different sky conditions, typical wavelet power spectra are calculated to quantify the timescale dependence of variability in global transmittance. Distinctly higher variability is observed at all frequencies in the power spectra of global transmittance under broken-cloud conditions compared to clear, cirrus, or overcast skies. The spatial autocorrelation function including its frequency dependence is determined to quantify the degree of similarity of two time series measurements as a function of their spatial separation. Distances ranging from 100 m to 10 km are considered, and a rapid decrease of the autocorrelation function is found with increasing frequency and distance. For frequencies above 1/3 min −1 and points separated by more than 1 km, variations in transmittance become completely uncorrelated. A method is introduced to estimate the deviation between a point measurement and a spatially averaged value for a surrounding domain, which takes into account domain size and averaging period, and is used to explore the representativeness of a single pyranometer observation for its surrounding region. Two distinct mechanisms are identified, which limit the representativeness; on the one hand, spatial averaging reduces variability and thus modifies the shape of the power spectrum. On the other hand, the correlation of variations of the spatially averaged field and a point measurement decreases rapidly with increasing temporal frequency. For a grid box of 10 km × 10 km and averaging periods of 1.5-3 h, the deviation of global transmittance between a point measurement and an area-averaged value depends on the prevailing sky conditions: 2.8 (clear), 1.8 (cirrus), 1.5 (overcast), and 4.2 % (broken clouds). The solar global radiation observed at a single station is found to deviate from the spatial average by as much as 14-23 (clear), 8-26 (cirrus), 4-23 (overcast), and 31-79 W m −2 (broken clouds) from domain averages ranging from 1 km × 1 km to 10 km × 10 km in area.

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Section: Spatial Representativeness Of a Point Measurementmentioning

confidence: 83%

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

et al. 2017

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“…These other potential error sources are numerous and include r e biases due to sub-pixel heterogeneity (Zhang and Plantnick, 2011;Zhang et al, 2012Zhang et al, , 2016; 3D radiative effects (Marshak et al, 2006); assumptions regarding the degree of cloud adiabaticity (f ad in Eqn. 10; Janssen et al, 2011;Merk et al, 2016); the choice of k value (assumed constant; Brenguier et al, 2011;Merk et al, 2016); the assumption of a vertically uniform N d ; the assumed droplet size distribution shape and width (Zhang, 2013); viewing geometry effects (Várnai and Davies, 1999;Horváth, 2004;Varnai and Marshak, 2007;Kato and Marshak, 2009;Liang et al, 2009;Di Girolamo et al, 2010;Maddux et al, 2010;Liang and Girolamo, 2013;Grosvenor and Wood, 2014;Liang et al, 2015;Bennartz and Rausch, 2017); upper level cloud and aerosol 10 layers (Haywood et al, 2004;Bennartz and Harshvardhan, 2007;Davis et al, 2009;Meyer et al, 2013;Adebiyi et al, 2015;Sourdeval et al, 2013Sourdeval et al, , 2016, etc. These errors have the potential to bias N d in a way that opposes the positive bias expected from the vertical penetration effect such that the overall biases may cancel out.…”

Section: Discussionmentioning

confidence: 99%

Quantifying and correcting the effect of vertical penetration assumptions on droplet concentration retrievals from passive satellite instruments

Grosvenor

Sourdeval

Wood

2018

Preprint

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Abstract. Droplet concentration (N d ) retrievals from passive satellite retrievals of cloud optical depth (τ ) and effective radius (r e ) 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 N d profile. Generally it is assumed that the retrieved r e value is that at the top of the cloud. In reality, barring r e retrieval biases due to cloud heterogeneity, etc., the retrieved r e is representative of that lower down in the cloud due to the vertical penetration of photons at the shortwave infra-red 5 wavelengths used to retrieve r e . This inconsistency will cause an overestimate of N d (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 (dτ ) for a range of idealised modelled adiabatic clouds using bispectral retrievals and plane-parallel radiative transfer. We find a tight relationship between dτ and τ and that a 1-D relationship approximates the modelled data well. Using this relationship we find that dτ values and hence N d biases are higher for the 2.1 µm channel r e retrieval (r e2.1 ) compared to the 3.7 µm one (r e3.7 ). 10The theoretical bias in the retrieved N d 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 N d bias rapidly reduces as cloud thickness increases, although still remains above 20 % for τ <19.8 and τ <7.7 for r e2.1 and r e3.7 , respectively. Californian stratocumulus regions produce fairly large overestimates due to the penetration depth bias with mean biases of 35-38 % for r e2.1 and 17-20 % for r e3.7 . For the other stratocumulus regions examined the errors are smaller (25-30 % for r e2.1 and 11-14 % for r e3.7 ). 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 r e2.1 and 40-60 % for r e3.7 . This shows that it is important 20 to apply a daily correction to N d 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

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“…In addition, the LUT is calculated for a plane-parallel cloud field using a 1-D radiative transfer model that does not consider the influence of the 3-D structure of clouds. However, Horváth (2004) found that no more than 17 % of the pixels containing marine liquid water clouds are plane-parallel objects, suggesting that the retrieval error arising from the solar-viewing geometry cannot be neglected (Zinner et al, 2010;Wolters et al, 2010;VantHull et al, 2007;Di Girolamo et al, 2010). The effects of cloud horizontal homogeneity also make the retrieval more complex.…”

Section: Introductionmentioning

confidence: 99%

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

et al. 2015

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Abstract. The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (∼ 1.5 µm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise.Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145 • ) are used to ensure retrievals of large droplet (> 15 µm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165 • are weak for cloud fields with CDR > 15 µm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

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Anisotropy of water cloud reflectance: A comparison of measurements and 1D theory

Cited by 36 publications

References 22 publications

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

Quantifying and correcting the effect of vertical penetration assumptions on droplet concentration retrievals from passive satellite instruments

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

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