AUTHOR=Ri Ana , Ma Run , Shang Huazhe , Xu Jian , Tana Gegen , Shi Chong , He Jie , Bao Yuhai , Chen Liangfu , Letu Husi TITLE=Influence of multilayer cloud characteristics on cloud retrieval and estimation of surface downward shortwave radiation JOURNAL=Frontiers in Environmental Science VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.857414 DOI=10.3389/fenvs.2022.857414 ISSN=2296-665X ABSTRACT=

Abstract: There are significant uncertainties in the retrieval accuracy of multilayer clouds with different phase states, leading to bias in the subsequent estimation of the surface downward shortwave radiation (DSR). Single-layer clouds are generally assumed for the retrieval of cloud optical and microphysical properties from satellite measurements, although multilayer clouds often occur in reality. In this article, the impact of multilayer clouds (thin ice clouds overlying lower-level water clouds) on the retrieval of cloud microphysical properties is simulated with the radiative transfer model RSTAR. The simulated results demonstrate the impact of double-layer clouds on the accuracy of retrieval of the cloud parameters and estimation of DSR. To understand the uncertainties of the input parameters, thorough sensitivity tests are simulated by RSTAR in the Results section. As compared with the retrieval results of single-layer clouds when the ice particle model of the upper-layer cloud is assumed to be ellipsoidal, the maximum relative bias in DSR is 0.63% when the COT for the ice cloud is 1.2 and for water cloud is 32.45. When the upper-layer ice cloud is assumed to be a hexagonal column, the maximum relative bias in DSR is 55.34% when the COT for the ice cloud is 2 and for the water cloud is 58.4. In addition, relative bias in DSR tends to increase both with radiance and ice cloud COT for a given radiance. This finding can provide a basis of reference for the estimation accuracy of radiative forcing in the IPCC report and the subsequent enhancement and improvement of retrieval algorithms.