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Atmosphere 2017, 8(3), 55; doi:10.3390/atmos8030055

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

1
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
2
Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric and Physics, Beijing 100029, China
3
National Meteorological Information Centre, China Meteorological Administration, Beijing 100081, China
4
Chinese Academy of Meteorological Sciences, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Academic Editor: Robert W. Talbot
Received: 4 January 2017 / Revised: 9 March 2017 / Accepted: 11 March 2017 / Published: 14 March 2017
(This article belongs to the Section Climatology and Meteorology)
View Full-Text   |   Download PDF [32148 KB, uploaded 15 March 2017]   |  

Abstract

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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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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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