CAJ | 학술논문

　　利用全球谱模式T106L19和增长模繁殖法（BGM）建立了月动力延伸集合预报系统，基于气候海表面温度（SST）和预测海表面温度，设计了三组集合预报试验，一组为气候SST作为模式下边界条件的集合预报试验（CSST试验），另一组为预测SST作为模式的下边界条件的集合预报试验（FSST试验），第三组为前两组试验的集合预报结果之和（AVE30试验），对两种海温强迫分别进行了48个月的试验，并对预报结果进行了检验和分析。结果表明：相对于单一的控制预报，不管是CSST试验还是FSST试验，利用BGM方法制作的初值集合预报能显著提高月平均环流的预报技巧，集合预报对PNA区域的预报技巧改进显著，特别是预测SST强迫有正的贡献；同时考虑初值和边值不确定性影响的集合预报试验（AVE30试验），其全球预报技巧不仅高于控制预报，也分别高于FSST试验和CSST试验，这说明要提高月延伸预报技巧，必须同时考虑初值和边值的影响；大气对SST强迫的响应在模式积分10天开始显著，SST对第二旬和第三旬的作用直接影响月平均环流的预报效果，而SST对第二旬和第三旬预报的影响不仅与SST本身变化有关，还与初值有关，不同的初值其作用不同；集合预报对我国夏季月平均温度分布具有较强预报能力，采用预报海温强迫的预报结果，总体上优于气候海温强迫的结果。
　　이용전구보모식T106L19화증장모번식법（BGM）건립료월동력연신집합예보계통，기우기후해표면온도（SST）화예측해표면온도，설계료삼조집합예보시험，일조위기후SST작위모식하변계조건적집합예보시험（CSST시험），령일조위예측SST작위모식적하변계조건적집합예보시험（FSST시험），제삼조위전량조시험적집합예보결과지화（AVE30시험），대량충해온강박분별진행료48개월적시험，병대예보결과진행료검험화분석。결과표명：상대우단일적공제예보，불관시CSST시험환시FSST시험，이용BGM방법제작적초치집합예보능현저제고월평균배류적예보기교，집합예보대PNA구역적예보기교개진현저，특별시예측SST강박유정적공헌；동시고필초치화변치불학정성영향적집합예보시험（AVE30시험），기전구예보기교불부고우공제예보，야분별고우FSST시험화CSST시험，저설명요제고월연신예보기교，필수동시고필초치화변치적영향；대기대SST강박적향응재모식적분10천개시현저，SST대제이순화제삼순적작용직접영향월평균배류적예보효과，이SST대제이순화제삼순예보적영향불부여SST본신변화유관，환여초치유관，불동적초치기작용불동；집합예보대아국하계월평균온도분포구유교강예보능력，채용예보해온강박적예보결과，총체상우우기후해온강박적결과。
A monthly dynamical extended-range ensemble forecast system is established with a global spectral model (T106L19) and an initial ensemble method of breeding of growing modes (BGM). Forty-eight examples of monthly integrations are performed with this system, and within each example, there are three sets of monthly ensemble forecasting experiments. The first set, named the CSST experiment, is forced by climatic sea surface temperatures (SSTs), and the second set, named the FSST experiment, is forced by predicted SSTs, while the last set, named the AVE30 experiment, is the mean of CSST and FSST. Then, the model results are verified and analyzed. Verifications show that the initial ensemble forecasts, based on BGM, can improve the monthly prediction skill remarkably when compared to a single control run, and it is especially precise for the Pacific and Northern America (PNA) region and the predicted SSTs have a positive contribution to the forecasts skill, particularly. The AVE30 experiment, that takes impacts of both initial uncertainties and boundary uncertainties into consideration, has a higher prediction skill than both the CSST and FSST experiments and suggests that we should attach more of an importance to roles of both initial conditions (ICs) and boundary conditions (BCs) to improve the monthly extended-range forecast skill. Meanwhile, analyzing the results indicate that atmospheric responses to SST forcing become significant after the tenth model integration day and the influences of SST forcing on the second and third ten-day period have a direct effect on the prediction skill of the monthly mean circulation. The influences of SST forcing on the second and third ten-day period relate to SSTs variation as well as ICs and the influences differ under different ICs. The monthly ensemble prediction system exhibits a strong capability of forecasting the monthly mean air temperature in China during the summer. The results of FSST forced by predicted SSTs prevail against those of CSST forced by climatic SSTs in general.