Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-771-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-771-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
27 Jan 2022
Development and technical paper |
| 27 Jan 2022
| 27 Jan 2022
Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3
Jinfang Yin
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather (LaSW), Chinese Academy of
Meteorological Sciences (CAMS), Beijing 100081, China
Xudong Liang
State Key Laboratory of Severe Weather (LaSW), Chinese Academy of
Meteorological Sciences (CAMS), Beijing 100081, China
Hong Wang
Guangzhou Institute of Tropical and Marine Meteorology, China
Meteorological Administration (CMA), Guangzhou 510080, China
Haile Xue
State Key Laboratory of Severe Weather (LaSW), Chinese Academy of
Meteorological Sciences (CAMS), Beijing 100081, China
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
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Short summary
An ensemble (EN) approach was designed to improve autoconversion (ATC) from cloud water to rainwater in cloud microphysics schemes. One unique feature of the EN approach is that the ATC rate is a mean value based on the calculations from several widely used ATC schemes. The ensemble approach proposed herein appears to help improve the representation of cloud and precipitation processes in weather and climate models.
An ensemble (EN) approach was designed to improve autoconversion (ATC) from cloud water to...
