Cloud heights retrieval from passive satellite measurements using lapse rate information

Abstract

Cloud top and base height (CTH and CBH) are essential in understanding the role of clouds on the weather and climate systems and improving radiation and precipitation simulations. However, inferring accurate cloud heights from passive satellite observations remains more challenging, especially for CBH. This study developed an effective and convenient method for estimating cloud heights for different cloud types on a global scale. The method is based on the mean lapse rate from surface to cloud top (Γ_ct), the lapse rate within (Γ_cb1) and below cloud (Γ_cb2), which are calculated from collocated active and passive satellite observations. The CTH and CBH can be easily derived based on cloud top temperature (CTT), surface temperature (ST), surface height (SH), Γ_ct, Γ_cb1 and Γ_cb2. The lapse rate method was applied to polar-orbiting and geostationary passive satellites and the performances were evaluated using cloud heights measurements from CloudSat and CALIPSO satellite. Overall, our retrieval results can achieve high accuracy and stability in estimating both CTH and CBH. For example, our CTH results have significantly improved the retrieval accuracy, with mean bias error (MBE) is 0 km and R is 0.96, and the absolute bias error (MAE) and root mean square error (RMSE) are reduced from 1.12 km and 1.72 km to 0.85 km and 1.33 km, respectively, compared with the MODIS CTH product. Our CBH retrieval results based on MODIS CTT and ST also agree well with CloudSat and CALIPSO observations, the R is 0.91 and the MAE, MBE and RMSE are 0.73 km, 0 km and 1.26 km, respectively. The cloud geometric thickness derived from the cloud heights retrieval results also agrees well with the active satellite observations (MAE = 0.97 km, MBE = 0 km, RMSE = 1.44 km and R = 0.91). In addition, the good performance of cloud heights retrieval during night and for geostationary satellites can further illustrate the excellent accuracy and strong applicability of the lapse rate method. Specifically, compared with SatCORPS Himawari-8 product, the MAE and RMSE of CTH (CBH) are reduced by 41.5 % (44.2 %) and 39.4 % (36.6 %), respectively. These statistical results confirm that our method has comparable performance to other algorithms (e.g., machine learning and other empirical methods), in the meantime, exhibiting the advantages of simplicity and less input parameters. In addition, the lapse rate method can also be employed to provide a supplemental criterion on determining cloud layers from radiosonde data.