Understanding Diurnal Cloud Cover Response using Satellite observations and Climate Simulations

Clouds play a fundamental role in determining the energy budget and hydrological cycle of Earth's atmosphere (Ramanathan et al. 1989, Slingo 1990, Bony et al. 2016, Su et al. 2017). Despite the progress on the observation and numerical modeling, cloud and cloud feedback remain as the dominant contributor to the uncertainties in climate models. Due to the short observational record, direct comparisons between model and observations on long-term cloud feedbacks are not yet possible. Recent studies have found a strong correlation between the model spread on short-term and long-term cloud feedbacks although the magnitude and spatial patterns are different (Zhou et al. 2015). Therefore, it is important to better constrain the short-term cloud feedbacks in climate models using observations. Following the method in Yue et al. (2019) the spatiotemporal variability of short-term cloud feedback is analyzed using the International Satellite Cloud Climatology Project (ISCCP) data (Norris et al. 2015) and compared with those from A-Train (Yue et al. 2019). The impact of cloud diurnal cycle on the cloud feedback is also quantified by different cloud types to understand the orbital sampling biases of A-Train on short-term cloud feedbacks.