Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

doi:10.1007/s11707-018-0728-6

Front. Earth Sci.

2018, Vol. 12

Issue (3) : 457-467 https://doi.org/10.1007/s11707-018-0728-6

RESEARCH ARTICLE

Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

Yan-An LIU^1,^2,^3,^4,⁵, Zhibin SUN^3,⁵(

), Maosi CHEN⁵, Hung-Lung Allen HUANG^3,⁶, Wei GAO^3,^4,⁵(

)

¹. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
². School of Geographic Sciences, East China Normal University, Shanghai 200241, China
³. ECNU-CSU Joint Research Institute for New Energy and the Environment, East China Normal University, Shanghai 200062, China
⁴. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, East China Normal University, Shanghai 200241, China
⁵. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, United States
⁶. Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI 53706, United States

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Abstract

The Atmospheric Infrared Sounder (AIRS) can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction (NWP) in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation (GSI) coupled with the Weather Research and Forecasting (WRF) model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases (Saola, Damrey, and Haikui in 2012) with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

Keywords AIRS WRF/GSI model radiance assimilation typhoon forecast

Corresponding Author(s): Zhibin SUN,Wei GAO

Just Accepted Date: 27 July 2018 Online First Date: 09 August 2018 Issue Date: 05 September 2018

Cite this article:

Yan-An LIU,Zhibin SUN,Maosi CHEN, et al. Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast[J]. Front. Earth Sci., 2018, 12(3): 457-467.

URL:

http://journal.hep.com.cn/fesci/EN/10.1007/s11707-018-0728-6
http://journal.hep.com.cn/fesci/EN/Y2018/V12/I3/457

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	Yan-An LIU
	Zhibin SUN
	Maosi CHEN
	Hung-Lung Allen HUANG
	Wei GAO

Fig.1 AIRS data coverage at different assimilation cycles for various analysis times (around±3 h) on 31 July, 2012. (a) 00 UTC; (b) 06 UTC; (c) 12 UTC; (d) 18 UTC.

Fig.2 Weighting functions of 120 AIRS channels assimilated by NCEP GDAS (dotted lines denote the channels discarded by model top; solid lines denote assimilated channels in regional model). Color used to distinguish the various channels. BT sensitivity is calculated with respect to the change of 1% for temperature.

Fig.3 Histogram of O-B with and without cloud detection for AIRS channel index of 253 (13.85 mm).

Fig.4 Innovation (O-B) distributions after the quality control for AIRS channel index of 1627 (7.01 mm).

Fig.5 Histogram of O-F (Observation-First Guess) before (blue) and after (red) bias correction for AIRS assimilated channels at 1800 UTC on July 30, 2012.

Fig.6 Bias comparisons of O-B and O-A for all 61 AIRS channels assimilated (the assimilation channel index corresponds to each image in Fig. 5). (a) 15 µm CO₂ channels between13.2 to15.4 mm; (b) Window channels between 8.8 to 12.6 mm; (c) H₂O channels between 6.2 to 8.2 mm; (d) Shortwave CO₂ channels between 3.8 to 4.6 mm.

Fig.7 Comparisons of temperature increment statistics at 500 hPa on July 30, 2012. (a) Exp experiment at 1200 UTC; (b) Ctrl experiment at 1200 UTC; (c) Exp experiment at 1800 UTC; (d) Ctrl experiment at 1800 UTC.

Fig.8 Comparisons of humidity increment statistics at 850 hPa on July 30, 2012. (a) Exp experiment at 1200 UTC; (b) Ctrl experiment at 1200 UTC; (c) Exp experiment at 1800 UTC; (d) Ctrl experiment at 1800 UTC.

Fig.9 Comparisons of absolute error of 72 h track forecast for Ctrl and Exp experiment with the best track provided by JTWC (one trial starting from 1800 UTC on July 30, 2012).

Fig.10 Comparisons of 72 h minimum sea level pressure forecast for Ctrl and Exp experiment with the intensity provided by JTWC (one trial starting from 1800 UTC on July 30, 2012).

Fig.11 Exp analysis minus Ctrl analysis. (a) Temperature at 500 hPa; (b) relative humidity at 850 hPa.

Fig.12 RMSE comparisons of three typhoon cases’ 72 h track forecast with (Exp) and without (Ctrl) AIRS radiances assimilation.

Fig.13 RMSE comparisons of three typhoon cases’ 72 h intensity (minimum sea level pressure) forecast with (Exp) and without (Ctrl) AIRS radiances assimilation.

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