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Estimating the vertical profiles of cloud water content in warm rain clouds
Author(s) -
Li Rui,
Guo Jingchao,
Fu Yunfei,
Min Qilong,
Wang Yu,
Gao Xiaoming,
Dong Xue
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023489
Subject(s) - precipitation , drizzle , weather research and forecasting model , cloud computing , environmental science , meteorology , satellite , atmospheric sciences , cloud top , geography , computer science , geology , engineering , aerospace engineering , operating system
The cloud water content (CWC) in rainy clouds is a crucial parameter to determine the onset and the growth rate of precipitation and to quantify the associated latent heating rate. No direct retrieval of CWC in rainy cloud from satellite observations is reported due to the difficulties of separating cloud particles from precipitation‐sized particles. However, based on multiple cloud simulations from the Weather and Research Forecasting (WRF) model, we have found that the CWC profile in warm rains can be well determined by three macrophysical cloud properties of cloud water path (CWP), cloud top height (CTH), and cloud bottom height (CBH). The CBH can be estimated using CWP, CTH, and near‐surface rain rate. We proposed an algorithm with a look‐up table for estimating the CWC profile using CWP, CTH, and near‐surface rain rate as inputs. The performance of this algorithm was tested with WRF model simulations and a real drizzle case observed by the CloudSat satellite. Testing verified that the algorithm can retrieve the vertical distribution of CWC correctly with few errors at different spatiotemporal scales. In addition, the algorithm is not confined to particular microphysics schemes and is valid for multiple cloud systems in different areas over the world. This algorithm is expected to improve current knowledge of cloud water content in rainy clouds.