Evaluation of Tropospheric Moisture Characteristics Among COSMIC-2, ERA5 and MERRA-2 in the Tropics and Subtropics

Global navigation satellite system (GNSS) radio occultation (RO) receivers onboard the recently-launched COSMIC-2 (C2) satellite constellation provide an unprecedented number of high vertical resolution moisture profiles throughout the tropical and subtropical atmosphere. In this study, the distribution and variability of water vapor was investigated using specific humidity retrievals from C2 observations and compared to collocated ERA5 and MERRA-2 reanalysis profiles within 40°N to 40°S from September to December 2019, which is prior to the assimilation of C2 in the reanalyses. Negative C2 moisture biases are evident within the boundary layer, so we focused on levels above the boundary layer in this study. Overall, C2 specific humidity shows excellent agreement with that of ERA5 and has larger differences with that of MERRA-2. In the tropical mid-troposphere, C2 shows positive biases compared to ERA5 (6–12%) and larger negative biases with MERRA-2 (15–30%). Strong correlations are observed between C2 and reanalysis specific humidity in the subtropics (>0.8) whereas correlations are slightly weaker in the deep tropics, especially for MERRA-2. Profile pairs with large moisture differences often occur in areas with sharp moisture gradients, highlighting the importance of measurement resolution. Locations which demonstrated weaker humidity correlations in active convection regions show that ERA5 has a negative specific humidity bias at 3 km in higher moisture environments, whereas MERRA-2 displays a large positive bias at 7 km. However, additional explanations for profile pairs with large moisture differences remain unclear and require further study.

A Review of Ice Cloud Optical Property Models for Passive Satellite Remote Sensing

The current wealth of spaceborne passive and active measurements from ultraviolet to the infrared wavelengths provides an unprecedented opportunity to construct ice cloud bulk optical property models that lead to consistent ice cloud property retrievals across multiple sensors and platforms. To infer the microphysical and radiative properties of ice clouds from these satellite measurements, the general approach is to assume an ice cloud optical property model that implicitly assumes the habit (shape) and size distributions of the ice particles in these clouds. The assumption is that this ice optical property model will be adequate for global retrievals. In this review paper, we first summarize the key optical properties of individual particles and then the bulk radiative properties of their ensemble, followed by a review of the ice cloud models developed for application to satellite remote sensing. We illustrate that the random orientation condition assumed for ice particles is arguably justified for passive remote sensing applications based on radiometric measurements. The focus of the present discussion is on the ice models used by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Clouds and Earth’s Radiant Energy System (CERES) science teams. In addition, we briefly review the ice cloud models adopted by the Polarization and Directionality of the Earth’s Reflectance (POLDER) and the Himawari-8 Advanced Himawari Imager (AHI) for ice cloud retrievals. We find that both the MODIS Collection 6 ice model and the CERES two-habit model result in spectrally consistent retrievals.