Evaluation of cloud properties from reanalyses over East Asia with a radiance-based approach
Abstract. Extensive observational and numerical investigations have been
performed to better characterize cloud properties. However, due to the large
variations in cloud spatiotemporal distributions and physical properties,
quantitative depictions of clouds in different atmospheric reanalysis
datasets are still highly uncertain. A radiance-based evaluation approach is
introduced and performed to evaluate the quality of cloud properties from reanalysis datasets. The China Meteorological Administration reanalysis (CRA); the
ECMWF fifth-generation reanalysis (ERA5); and the Modern-Era Retrospective
analysis for Applications, Version 2 (MERRA-2), i.e., those reanalyses providing
sufficient cloud information, are considered. To avoid the influence of
assumptions and uncertainties on satellite retrieval algorithms, forward radiative transfer simulations are used as a bridge to translate the
reanalyses to corresponding radiances that are expected to be observed by
satellites. The simulated reflectances and brightness temperatures (BTs) are
directly compared with observations from the Advanced Himawari Imager
onboard the Himawari-8 satellite in the East Asia region. We find that the
simulated reflectances and BTs based on CRA and ERA5 are close to each
other. CRA represents the total and midlayer cloud cover better than the other
two datasets, and ERA5 depicts deep-convection structures more closely than
CRA does. Comparisons of the simulated and observed BT differences suggest that
water clouds are generally overestimated in ERA5 and MERRA-2, and MERRA-2
also overestimates the ice clouds over cyclone centers. Overall, clouds
from CRA, ERA5, and MERRA-2 show their own advantages in different aspects.
The ERA5 reanalysis has the best capability to represent the cloudy
atmospheres over East Asia, and the CRA representations are close to those
in ERA5.