Parameterizing Surface Downwelling Longwave Radiation under Single Layer Water and ice clouds based on Cloud properties from Ground based remote sensing

The Meteorological  Observatory Lindenberg, a key site in the Baseline Surface Radiation Network (BSRN), has provided continuous measurements of surface shortwave (SW) and longwave (LW) radiation for 30 years. As an ACTRIS national remote sensing facility, it also offers over 20 years of Cloudnet products. Together, these long-term datasets form a critical resource for cloud and radiation studies that enable detailed investigations into how different cloud macrophysical and microphysical properties affect surface SW and LW radiation.This study focuses on parameterizing downward longwave (LW↓) radiation at the surface using the combined BSRN and Cloudnet datasets under single-layer ice and water cloud conditions. Previous studies have developed LW↓ parameterizations for all-sky conditions, using variables such as cloud fraction, cloud base temperature, and liquid water path (Trigo et al., 2010; Schmetz et al., 1986; Gupta et al., 2010; Zhou et al., 2007). However, many of these parameterizations were based on satellite data, where retrieval of cloud base height involves indirect methods and introduces significant uncertainties, potentially affecting the accuracy of surface LW↓ estimates (Yun Jiang et al., 2023; Yu et al., 2025). While ground-based datasets have primarily been used for validation, their continued importance for methodological development is emphasized in recent work (Feng Yang et al., 2020).We begin by calculating the LW cloud radiative effect (CRE) at the surface as the difference in radiative flux between all-sky and cloud-free conditions (e.g., Cronin et al., 2006). In this study, cloud-free LW↓ radiation is estimated using the Dupont parameterization, which relies on atmospheric temperature and integrated water vapor profiles (Dupont et al., 2008).The resulting LW CRE values are then correlated with cloud macrophysical and microphysical properties to examine their influence on surface LW↓ radiation. Statistical analyses are performed to identify the cloud parameters most significantly affecting LW↓, guiding the selection of variables for parameterization. Finally, we present two distinct parameterizations for surface LW↓ radiation under single-layer water and ice cloud conditions, based on the cloud properties determined to have the greatest impact.