Understanding the Microphysical Control and Spatial‐Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations. Issue 10 (24th May 2022)

• Record Type: Journal Article
• Authors: Zhang, Zhibo; Oreopoulos, Lazaros; Lebsock, Matthew D.; Mechem, David B.; Covert, Justin
• Is Part Of: Geophysical research letters. Volume 49:Issue 10(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-24
• Subjects: warm rain -- probability of precipitation -- CloudSat -- MODIS; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2022GL098863
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial‐temporal variation of grid‐mean in‐cloud can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models. Plain Language Summary: We use satellite observations to understand the probability of warm rain in low‐level marine boundary layer clouds. We found that the probability of warm rain can be parameterized as a logistic function of cloud droplet number concentration and cloud water path. This parameterization can help us understand how the probability of warm rain changes from one cloud regime to another and from one month to another. Key Points: A parameterization scheme developed to quantify variation of warm rain probability as a function of cloud droplet number and water path The transition of warm rain probability from stratocumulus to cumulus regime is associated more strongly with variation of droplet number The annual cycle of warm rain probability is associated more strongly with cloud water path variations