Comparing FY-2F/CTA products to ground-based manual total cloud cover observations in Xinjiang under complex underlying surfaces and different weather conditions

Author:

Li Shuai,Zhang HuaORCID,Chen Yonghang,Wang ZhiliORCID,Li Xiangyu,Li Yuan,Xue Yuanyuan

Abstract

Abstract. Clouds are an important parameter of artificial water augmentation, which is of substantial significance to judge the precipitation capacity. Xinjiang is an arid region in northwestern China, where weather stations are sparsely distributed, the types of underlying surface are complex, and the climate between the southern and northern region varies greatly. However, the retrieval of the total cloud cover (TCC) from satellite in arid areas is a challenging task. Based on the TCC data observed by ground observation stations (GOSs) from June 2015 to May 2016 considering the complex underlying surfaces and different weather conditions, the precision, consistency, and error between the cloud total amount from the FengYun-2F stationary satellite (FY-2F/CTA) and manually observed TCC are compared and evaluated in the Xinjiang region. The findings of this study are as follows: (1) the precision rate (PR) of FY-2F/CTA in the Xinjiang region is 75.6 %, which gradually decreases from north to south, demonstrating a high false rate (FR) and a low missing rate (MR). The consistency rate (CR) is 51.5 %, with little difference among three subregions of Xinjiang, all showing a high weak rate (WR) and low strong rate (SR), which means that the TCC values inverted from FY-2 satellite data are generally lower than those observed by GOSs, especially in southern Xinjiang. The bias is −20 %, and all the error indexes (EIs) including bias, MAE, and RMSE increase from central to the north and south of Xinjiang; that means the EIs are the lowest in Tianshan and the highest in southern Xinjiang. FY-2F/CTA exhibits higher PR and CR in the underlying surface of vegetation compared to non-vegetation; that is to say that FY-2F/CTA performs best in the underlying surfaces of forest and plowland, while their performance is relatively poorer in the underlying surface of snow and ice. (2) With rising temperature the PR and CR of FY-2F/CTA increase, while the EIs decrease. Under various temperature conditions, FY-2F/CTA has always exhibited high MR, low FR (on the contrary in January), high WR, and low SR. From low elevation to high elevation, the PR and CR of FY-2F/CTA decrease, but the PR increases significantly when the altitude is higher than 2000 m. (3) Dust reduces the CR of FY-2F/CTA and increases their WR and MR but has a relatively minor impact on the identification of cloud and non-cloud. (4) Under different cloud cover levels, the PR and EIs of FY-2F/CTA are directly proportional to the amount of TCC, while the CR is inversely proportional to it: that is, the CR is higher and the PR and EIs are lower under clear-sky and partly cloudy conditions, and the CR is lower and the PR and EIs are higher under cloudy and overcast conditions. This study assessed the FY-2F/CTA under various conditions in arid areas of Xinjiang, including complex underlying surface, various temperature and altitude, dust effects, and different cloud cover levels. Thus, the research finding could serve as a valuable reference for satellite-based retrieval and applications related to TCC in arid regions.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Chinese Academy of Meteorological Sciences

Publisher

Copernicus GmbH

Reference46 articles.

1. Betts, A. K., Desjardins, R., Worth, D., and Beckage, B.: Climate coupling between temperature, humidity, precipitation, and cloud cover over the Canadian Prairies, J. Geophys. Res.-Atmos., 119, 13305–13306, https://doi.org/10.1002/2014JD022511, 2014.

2. Boers, R., Acarreta, J. A., and Gras, J. L.: Satellite monitoring of the first indirect aerosol effect: Retrieval of the droplet concentration of water clouds, J. Geophys. Res., 111, D22208, https://doi.org/10.1029/2005JD006838, 2006.

3. Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S., Dufresne, J. L., Hall, A., Hallegatte, S., Holland, M. M., Ingram, W., Randall, D. A., Soden, B. J., Tselioudis, G., and Webb, M. J.: How well do we understand and evaluate climate change feedback processes?, J. Climate, 19, 3445–3482, https://doi.org/10.1175/JCLI3819.1, 2006.

4. Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus, R., Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H., Watanabe, M., and Webb, M. J.: Clouds, circulation and climate sensitivity, Nat. Geosci., 8, 261–268, https://doi.org/10.1038/ngeo2398, 2015.

5. Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V. M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Doschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P. M., Cambridge University Press, Cambridge, 571–657, ISBN: 978-1-009-41954-3, 2013.

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