Evaluation of the Forecast Accuracy of Near-Surface Temperature and Wind in Northwest China Based on the WRF Model
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This study investigated the performance of the mesoscale Weather Research and Forecasting (WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in June and December 2015. The spatial distribution of the monthly average bias errors in the forecasts of 2-m temperature and 10-m wind speed is analyzed first. It is found that the forecast errors for 2-m temperature and 10-m wind speed in June are strongly correlated with the terrain distribution. However, this type of correlation is not apparent in December, perhaps due to the inaccurate specification of the surface albedo and freezing–thawing process of frozen soil in winter in Northwest China in the WRF model. In addition, the WRF model is able to reproduce the diurnal variation in 2-m temperature and 10-m wind speed, although with weakened magnitude. Elevations and land-use types have strong influences on the forecast of near-surface variables with seasonal variations. The overall results imply that accurate specification of the complex underlying surface and seasonal changes in land cover is necessary for improving near-surface forecasts over Northwest China.
Key wordsWeather Research and Forecasting (WRF) model complex terrain near-surface forecasts diurnal variation
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We appreciate the constructive comments and suggestions from the two anonymous reviewers.
- Byun D., F. Ngan, X. S. Li, et al., 2008: Evaluation of Retrospective MM5 and CMAQ Simulation of TexAQS-II Period with CAMS Measurements. Texas Commission on Environmental Quality Final Rep., Grant No. 582-5-64594-FY07-02, 30 pp.Google Scholar
- Cao F. Q., L. Dan, and Z. G. Ma, 2015: Simulative study of the impact of the cropland change on the regional climate over China. Acta Meteor. Sinica, 73, 128–141, doi: 10.11676/qxxb2015.001. (in Chinese)Google Scholar
- Chen H. S., X. Li, and W. J. Hua, 2015: Numerical simulation of the impact of land use/land cover change over China on regional climates during the last 20 years. Chinese J. Atmos. Sci., 39, 357–369, doi: 10.3878/j.issn.1006-9895.1404.14114. (in Chinese)Google Scholar
- He J. J., Y. Yu, N. Liu, et al, 2014: Impact of land surface information on WRF’s performance in complex terrain area. Chinese J. Atmos. Sci., 38, 484–498, doi: 10.3878/j.issn.1006-9895. 2013.13186. (in Chinese)Google Scholar
- Hu, X.-M., P. M. Klein, and M. Xue, 2013: Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments. J. Geophys. Res., 118, 10490–10505, doi: 10.1002/jgrd.50823.Google Scholar
- Liu J. Y., W. H. Kuang, Z. X. Zhang, et al., 2014: Spatiotemporal characteristics, patterns and causes of land-use changes in China since the late 1980s. Acta Geogra. Sinica, 69, 3–14, doi: 10.11821/dlxb201401001. (in Chinese)Google Scholar
- Oke T. R., 1987: Boundary Layer Climates. Cambridge University Press, Cambridge, 435 pp.Google Scholar
- Pan X. D., X. Li, Y. H. Ran, et al., 2012: Impact of underlying surface information on WRF modeling in Heihe River basin. Plateau Meteor., 31, 657–667. (in Chinese)Google Scholar
- Santos-Alamillos F. J., D. Pozo-Vázquez, J. A. Ruiz-Arias, et al., 2013: Analysis of WRF model wind estimate sensitivity to physics parameterization choice and terrain representation in Andalusia (southern Spain). J. Appl. Meteor. Climatol., 52, 1592–1609, doi: 10.1175/JAMC-D-12-0204.1.CrossRefGoogle Scholar
- Sheng L. F., K. H. Schlunzen, and Z. M. Wu, 2000: Three-dmensional numerical simulation of the mesoscale wind structure over Shandong Peninsula. Acta Meteor. Sinica, 14, 98–107.Google Scholar
- Tao S. Y., 1980: Heavy Rainfalls in China. Science Press, Beijing, 225 pp. (in Chinese)Google Scholar
- Wang C. H., and S. L. Jin, 2013: Error features and their possible causes in simulated low-level winds by WRF at a wind farm. Wind Energy, 17, 1315–1325, doi: 10.1002/we.1635.Google Scholar
- Whiteman C. D., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, Oxford, 355 pp.Google Scholar
- Wu Z. M., and K. H. Schlunzen, 1992: Numerical study on the local wind structures forced by the complex terrain of Qingdao area. Acta Meteor. Sinica, 6, 355–366.Google Scholar
- Zhang Y., X. Y. Wen, and C. J. Jang, 2010: Simulating chemistry–aerosol–cloud–radiation–climate feedbacks over the continental U.S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF/Chem). Atmos. Environ., 44, 3568–3582, doi: 10.1016/j.atmosenv.2010.05.056.CrossRefGoogle Scholar
- Zheng D., R. van der Velde, Z. Su, et al., 2017: Evaluation of Noah frozen soil parameterization for application to a Tibetan Meadow Ecosystem. J. Hydrometeor., doi: 10.1175/JHM-D-16-0199.1.Google Scholar