View‐angle‐dependent AIRS cloudiness and radiance variance: Analysis and interpretation

Abstract

[1] Upper tropospheric clouds play an important role in the global energy budget and hydrological cycle. Significant view-angle asymmetry has been observed in upper-level tropical clouds derived from 8 years of Atmospheric Infrared Sounder (AIRS) 15 mm radiances. Here we find that the asymmetry also exists in the extratropics. It is larger during day than that during night, more prominent near elevated terrain, and closely associated with deep convection and wind shear. The cloud radiance variance, a proxy for cloud inhomogeneity, has consistent characteristics of the asymmetry to those in the AIRS cloudiness. The leading causes of the view-dependent cloudiness asymmetry are the local time difference and small-scale organized cloud structures. The local time difference (1-1.5 h) of upper-level clouds between two AIRS outermost views can create parts of the observed asymmetry. On the other hand, small-scale tilted and banded structures of the upper-level clouds can induce about half of the observed view-angle-dependent differences in the AIRS cloud radiances and their variances. This estimate is inferred from analogous study using microwave humidity sounder radiances observed during the period of time when there were simultaneous measurements at two different view-angles from NOAA-18 and NOAA-19 satellites. The existence of tilted cloud structures and asymmetric 15 mm and 6.7 mm cloud radiances implies that cloud statistics would be view-angle-dependent, and should be taken into account in radiative transfer calculations, measurement uncertainty evaluations and cloud climatology investigations. In addition, the momentum forcing in the upper troposphere from tilted clouds is also likely asymmetric, which can affect atmospheric circulation anisotropically.

CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

“…The NOAA IWP has been reported to have significantly low values compared with radar and IR measurements (Holl et al, 2010;Eliasson et al, 2011). As an extended product, rain rate is derived from the retrieved IWP with an empirical polynomial relationship (Ferraro, 2007). The operational NOAA IWP data, now integrated into the MSPPS in the CLASS website, will also be used in this study for comparisons.…”

“…Warmer T B values are mostly from the clear sky or surface, while colder T B are the cases of ice clouds or snow/icy surfaces at a high elevation. The T B PDFs all have a broad peak with a standard deviation (σ ) that is so wide that the empirical 3σ cloud detection method (i.e., T B peak − 3σ < 0 for cloud detection) used by many previous studies does not work well when applied directly to the T B data (e.g., McNally et al, 2006;Gong and Wu, 2013). On the other hand, the T cir PDFs have a smaller standard deviation because the CRTM-derived T ccr from MERRA data has removed a lot of clear-sky variability (Fig.…”

Meridionally-tilted ice cloud structures in the tropical Upper Troposphere as seen by CloudSat

“…For example, they partially account for the anisotropy of the cloud radiative forcing (Fu et al, 2000;Gong and Wu, 2013) and modulate the hydrological cycle (Naud et al, 2010). Neglecting or misrepresenting the cloud tilt induces additional biases in satellite retrieval of cloud properties (e.g., Hong et al, 2005) and increases uncertainty of model CRE estimation (e.g., Li and Barker, 2002). In GCM, cloud slantwise tilt is tied to the "overlap" parameter, which is assumed to be "maximum-random" globally in most GCMs to achieve the desired cloud fraction or radiation balance.…”

CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

“…Contamination of cloud ice retrievals was also found over snowy/icy surfaces (Wu et al, 2009). While further improvements are still needed for ice scattering calculation in the microwave RTMs, empirical forward models have been used for cloud retrievals (Holl et al, 2010). Empirical approaches establish some ad hoc relationships between cloud ice variables and radiance/reflectivity measurements from the data themselves.…”