The model ability to predict summer precipitation at seasonal time scale in China is evaluated by using the re-forecast data during 1996-2015 from the BCC second-generation short-range climate forecast system with the lead time of 1~3 months, and the interannual differences of model's prediction ability are analyzed. The possible causes of model prediction errors are also discussed. The results show that the model has a certain seasonal forecasting ability for summer precipitation in China, it has high seasonal forecasting skill over southwest China, the middle and lower reaches of the Yangtze River, west of Huanghuai Plain, North China and Northern Tibet Plateau. Generally speaking, the model has good prediction ability for precipitation anomalies in China. The anomaly sign consistency is high in middle and lower reaches of the Yangtze river, Huanghuai area, South China, Northwest China and northern part of North China. However, there are also some deviations, which are mainly manifested in the less precipitation in East China predicted by the model, the limited forecasting skills for summer precipitation anomalies and the large differences of prediction ability in different years. The predicted high temperature areas in western Pacific and Indian Ocean SST is limited, the intensity of the subtropical high and water vapor convergence is significantly weak, which lead to the less precipitation in East China. Judging from the interannual differences in model's prediction ability, when the precipitation in South China is more than normal years, and the precipitation in the middle and lower reaches of the Yangtze River and North China is less, the model has higher prediction skills. On the contrary, the forecast skill is lower. The analyses of the relationship between summer precipitation in East China and sea surface temperature show that the Northwest Pacific Ocean, the tropical western Pacific and the North Indian Ocean are three key areas for summer precipitation prediction in East China and the SST biases in the Northwest Pacific Ocean have important effects on the model's forecasting skills. The mutual configuration of SST, geopotential height, wind field and water vapor flux divergence field leads to the distribution and intensity difference of summer precipitation in East China, but the model cannot reasonably capture the relationship between them, thus reduce the model's ability to predict summer precipitation in East China. Therefore, accurate prediction on the relationship between external forcing factors and precipitation anomalies is important for the improvement of the precipitation forecasting skills in China.
[1]Gao X J, Wang M L, Filippo G, et al, 2013. Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0[J]. Atmospheric and Oceanic Science Letters, 6(5):381-386. DOI:10.3878/j.issn.1674-2834.13.0029.
[2]Kanamitsu M, Ebisuzaki W, Woollen J, et al, 2002. NCEP-DOE AMIP-II reanalysis (R-2)[J]. Bulletin of the American Meteorological Society, 83(11):1631-1643. DOI:10.1175/BAMS-83-11-1631.
[3]Krishnamurti T N, Mitra A K, Kumar T S V V, et al, 2006. Seasonal climate, forecasts of the South Asian monsoon using multiple coupled models[J]. Tellus A:Dynamic Meteorology and Oceanography, 58(4):487-507. DOI:10.1111/j.1600-0870.2006.00184. x.
[4]Kumar V, Krishnamurti T N, 2012. Improved seasonal precipitation forecasts for the Asian monsoon using 16 atmosphere-ocean coupled models. Part I:Climatology[J]. Journal of Climate, 25(1):39-64. DOI:10.1175/2011JCLI4125.1.
[5]Murray R J, 1996. Explicit generation of orthogonal grids for ocean models[J]. Journal of Computational Physics, 126(2):251-273. DOI:10.1006/jcph. 1996.0136.
[6]Reynolds R W, Rayner N A, Smith T M, et al, 2002. An improved in situ and satellite SST analysis for climate[J]. Journal of Climate, 15(13):1609-1625. DOI:10.1175/1520-0442(2002)015＜1609:AIISAS>2.0. CO; 2.
[7]Wu J, Ren H L, Zuo J Q, et al, 2016. MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model[J]. Dynamics of Atmospheres and Oceans, 75:78-90. DOI:10.1016/j.dynatmoce. 2016.06.001.
[8]Wu T W, Li W P, Jin J J, et al, 2013. Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century[J]. Journal of Geophysical Research:Atmophere, 118:4326-4347. DOI:10.1002/jgrd. 50320, 2013.
[9]Wu T W, Yu R C, Zhang F, et al, 2010. The Beijing Climate Center atmospheric general circulation model:Description and its performance for the present-day climate[J]. Climate Dynamics, 34:123-147. DOI:10.1007/s00382-008-0487-2.
[10]Xin X G, Wu T W, Li J L, et al, 2013. How well does BCC_CSM1.1 reproduce the 20th century climate change over China?[J]. Atmospheric and Oceanic Science Letters, 6(1):21-26. DOI:10.1080/16742834.2013.11447053.
[11]Yang S, Wen M, Yang R Q, et al, 2011. Impacts of land process on the onset and evolution of Asian summer monsoon in the NCEP climate forecast system[J]. Advances in Atmospheric Science, 28(6):1301-1317. DOI:10.1007/s00376-011-0167-8.
[12]Saha S, Moorthi S, Wu X R, et al, 2014. The NCEP climate forecast system version 2[J]. Journal of Climate, 27:2185-2208. DOI:10.1175/JCLI-D-12-00823.1.
[13]丁一汇, 刘一鸣, 宋永加, 等, 2002.我国短期气候动力预测模式系统的研究及试验[J].气候与环境研究, 7(2):236-246. DOI:10.3878/j.issn.1006-9585.2002.02.11.
[14]丁一汇, 李清泉, 李维京, 等, 2004.中国业务动力季节预报的进展[J].气象学报, 62(5):598-612. DOI:10.11676/qxxb2004.059.
[15]丁一汇, 2011.季节气候预测的进展和前景[J].气象科技进展, 1(3):14-27.
[16]董敏, 吴统文, 左群杰, 等, 2018.气候系统模式对南亚高压气候特征的模拟比较研究[J].高原气象, 37(2):455-468. DOI:10.7522/j.issn.1000-0534.2017.00051.
[17]顾伯辉, 郑志海, 封国林, 等, 2017.季节预测模式对东亚夏季环流的预测能力及其对热带海洋的响应分析[J].大气科学, 41(1):91-105. DOI:10.3878/j.issn.1006-9895.1603.15154.
[18]郭渠, 刘向文, 吴统文, 等, 2017.基于BCC_CSM模式的中国东部夏季降水预测检验及订正[J].大气科学, 41(1):71-90. DOI:10.3878/j.issn.1006-9895.1602.15280.
[19]孔德璿, 2013.贵阳市汛期降水预报方法的研究[C]//创新驱动发展提高气象灾害防御能力——S6短期气候预测理论、方法与技术.南京: 气象出版社, 263-275.
[20]李维京, 张培群, 李清泉, 等, 2005.动力气候模式预测系统业务化及其应用[J].应用气象学报, 16(增刊):1-11. DOI:10.3969/j.issn.1001-7313.2005.z1.001.
[21]李维京, 郑志海, 孙丞虎, 2013.近年来我国短期气候预测中动力相似预测方法研究与应用进展[J].大气科学, 37(2):341-350. DOI:10.3878/j.issn.1006-9895.2012.12311.
[22]吴捷, 任宏利, 张帅, 等, 2017. BCC二代气候系统模式的季节预测评估和可预报性分析[J].大气科学, 41(6):1300-1315. DOI:10.3878/j.issn.1006-9895.1703.16256.
[23]吴统文, 宋连春, 刘向文, 等, 2013.国家气候中心短期气候预测模式系统业务化进展[J].应用气象学报, 24(5):533-543. DOI:10.3969/j.issn.1001-7313.2013.05.003.
[24]吴统文, 宋连春, 李伟平, 等, 2014.北京气候中心气候系统模式研发进展-在气候变化研究中的应用[J].气象学报, 72(1):12-29. DOI:10.11676/qxxb2013.084.
[25]余丹丹, 张韧, 赵越超, 等, 2014.西太平洋副高的东西进退与东亚夏季风系统的相互影响与关联[J].大气科学学报, 37(3):304-312.
[26]张磊, 王春燕, 潘小多, 2018.基于区域气候模式未来气候变化研究综述[J].高原气象, 37(5):1440-1448. DOI:10.7522/j.issn.1000-0534.2018.00018.
