View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

Abstract

We investigated the view angle dependence of domain mean Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) and that of corresponding cloud optical thickness, effective radius, and liquid cloud fraction as proxy for plane-parallel retrieval biases. Independent Advanced Microwave Scanning Radiometer-EOS LWP was used to corroborate that the observed variations with sun-view geometry were not severely affected by seasonal/latitudinal changes in cloud properties. Microwave retrievals showed generally small (<10%) cross-swath variations. The view angle (cross-swath) dependence of MODIS optical thickness was weaker in backscatter than forward scatter directions and transitioned from mild ∩ shape to stronger ∪ shape as heterogeneity, sun angle, or latitude increased. The 2.2 μm effective radius variations always had a ∪ shape, which became pronounced and asymmetric toward forward scatter in the most heterogeneous clouds and/or at the lowest sun. Cloud fraction had the strongest and always ∪-shaped view angle dependence. As a result, in-cloud MODIS cloud liquid water path (CLWP) showed surprisingly good view angle (cross-swath) consistency, usually comparable to that of microwave retrievals, due to cancelation between optical thickness and effective radius biases. Larger (20-40%) nadir-relative increases were observed in the most extreme heterogeneity and sun angle bins, that is, typically in the polar regions, which, however, constituted only 3-8% of retrievals. The good consistency of MODIS in-cloud CLWP was lost for gridbox mean LWP, which was dominated by the strong cloud fraction increase with view angle. More worryingly, MODIS LWP exhibited significant and systematic absolute increases with heterogeneity and sun angle that is not present in microwave LWP.

Simulation of Bidirectional Reflectance in Broken Clouds: From Individual Realization to Averaging over an Ensemble of Cloud Fields

“…It is shown that, besides such characteristics as the averaging scale, instrument/orbit properties, etc., the results of retrieving COD and REF depend strongly on sun-view geometry and cloud heterogeneity. This is confirmed by the simulation results in 2D and 3D cloud models [38,[40][41][42][43][44][45][46].…”

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

“…CPR data were used for rain detection, whereas CALIOP cloud top temperature data served to identify warm cloud conditions. The adiabatic assumption (e.g., Greenwald, ) was applied to the MODIS 0.86‐μm optical thickness/3.7‐μm effective radius all‐sky CWP products for solar zenith angles ≤45°, which represents the most conservative threshold when noticeable biases begin to occur in these products (Greenwald, ; Grosvenor & Wood, ; Horváth et al, ; Lebsock & Su, ). The 3.7‐μm effective radius data were chosen because they are less impacted by drizzle (Lebsock et al, ) and cloud inhomogeneities (e.g., Painemal, Minnis, & Sun‐Mack, ; Zhang et al, ) than other wavelengths.…”

Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations

“…A variety of observational case studies and process studies were also published using similar approaches for deriving CDNC (Boers et al, 2006;George and Wood, 2010;Painemal and Zuidema, 2010;Rausch et al, 2010;. Various authors have addressed shortcomings and issues related to CDNC climatologies (Merk et al, 2016;Grosvenor and Wood, 2014) as well as issues related to the cloud retrievals underlying the CDNC climatologies (Zhang and Platnick, 2011;Nakajima et al, 2010;Maddux et al, 2010;Horvath et al, 2014). Painemal and Zuidema (2011) validate MODIS-derived CDNC against in situ observations taken in the South Pacific during VOCALS-Rex (Wood et al, 2011).…”