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Open AccessArticle

A Case Study of Assimilating Lightning-Proxy Relative Humidity with WRF-3DVAR

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Key Laboratory of Arid Climatic Changing and Reducing Disaster of Gansu Province, College of Atmospheric Sciences, Lanzhou University, No.222 TianShui South Road, Lanzhou 730000, China
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Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric and Physics, Beijing 100029, China
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National Meteorological Information Centre, China Meteorological Administration, Beijing 100081, China
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Chinese Academy of Meteorological Sciences, Beijing 100081, China
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Author to whom correspondence should be addressed.
Academic Editor: Robert W. Talbot
Atmosphere 2017, 8(3), 55; https://doi.org/10.3390/atmos8030055
Received: 4 January 2017 / Revised: 9 March 2017 / Accepted: 11 March 2017 / Published: 14 March 2017
(This article belongs to the Section Meteorology)
Lightning network data, considered as a useful supplement to radar observations, are a good indicator of severe convection, and has high temporal and spatial resolution. In Numerical Weather Prediction (NWP) models, lightning data are a new source of data to improve the forecasting of convective systems. In this case study, lightning data assimilation is conducted by converting lightning data to water vapor mixing ratio via a simple smooth continuous function, with input variables of total flash rate and simulated graupel mixing ratio at 9 km gridded resolution. Relative humidity converted from the retrieved water vapor mixing ratio is assimilated into the background field utilizing the three-dimensional variational (3DVAR) method in WRFDA (the Weather Research and Forecasting model Data Assimilation system). The benefits of assimilating lightning data are demonstrated in a series of experiments using data from a strong convection event that affected Beijing, Tianjin, Hebei and Shandong Province, on 31 July 2007. A nested domain with resolutions of 9 km and 3 km is implemented. For this case, assimilating lightning data shows some improvements in predictions of both reflectivity and neighboring precipitation, and in the temperature, dew-point temperature and relative humidity profile after seven hours. View Full-Text
Keywords: lightning; assimilation; relative humidity; 3DVAR lightning; assimilation; relative humidity; 3DVAR
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MDPI and ACS Style

Wang, Y.; Yang, Y.; Liu, D.; Zhang, D.; Yao, W.; Wang, C. A Case Study of Assimilating Lightning-Proxy Relative Humidity with WRF-3DVAR. Atmosphere 2017, 8, 55.

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