Influence of future tropical cyclone track changes on their basin-wide intensity over the western North Pacific: Downscaled CMIP5 projections     

Chao Wang  Liguang Wu 《大气科学进展》2015,32(5):613-623

The possible changes of tropical cyclone(TC) tracks and their influence on the future basin-wide intensity of TCs over the western North Pacific(WNP) are examined based on the projected large-scale environments derived from a selection of CMIP5(Coupled Model Intercomparison Project Phase 5) models. Specific attention is paid to the performance of the CMIP5 climate models in simulating the large-scale environment for TC development over the WNP. A downscaling system including individual models for simulating the TC track and intensity is used to select the CMIP5 models and to simulate the TC activity in the future.The assessment of the future track and intensity changes of TCs is based on the projected large-scale environment in the21 st century from a selection of nine CMIP5 climate models under the Representative Concentration Pathway 4.5(RCP4.5)scenario. Due to changes in mean steering flows, the influence of TCs over the South China Sea area is projected to decrease,with an increasing number of TCs taking a northwestward track. Changes in prevailing tracks and their contribution to basin-wide intensity change show considerable inter-model variability. The influences of changes in prevailing track make a marked contribution to TC intensity change in some models, tending to counteract the effect of SST warming. This study suggests that attention should be paid to the simulated large-scale environment when assessing the future changes in regional TC activity based on climate models. In addition, the change in prevailing tracks should be considered when assessing future TC intensity change.  相似文献   

Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling     

Kun-Hui Ye  Chi-Yung Tam  Wen Zhou  Soo-Jin Sohn 《大气科学进展》2015,32(5):680-689

The performances of various dynamical models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) in predicting station-scale rainfall in South China(SC) in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME's ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output(DMO) over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.  相似文献   

Can Artificial Climate Trends in Global Reanalysis be Reduced by Dynamical Downscaling:A Case Study of China          下载免费PDF全文

ZHAO Tian-Bao  ZHAO De-Ming 《大气和海洋科学快报》2011,4(1):30-35

In this study,the ability of dynamical downscaling for reduction of artificial climate trends in global reanalysis is tested in China.Dynamical downscaling is performed using a 60-km horizontal resolution Regional Integrated Environmental Model System (RIEMS) forced by the NCEP-Department of Energy (DOE) reanalysis II (NCEP-2).The results show that this regional climate model (RCM) can not only produce dynamically consistent fine scale fields of atmosphere and land surface in the regional domain,but it also has the ability to minimize artificial climate trends existing in the global reanalysis to a certain extent.As compared to the observed 2-meter temperature anomaly averaged across China,our model can simulate the observed inter-annual variation and variability as well as reduce artificial climate trends in the reanalysis by approximately 0.10 C decade 1 from 1980 to 2007.The RIEMS can effectively reduce artificial trends in global reanalysis for areas in western China,especially for regions with high altitude mountains and deserts,as well as introduce some new spurious changes in other local regions.The model simulations overestimated observed winter trends for most areas in eastern China with the exception of the Tibetan Plateau,and it greatly overestimated observed summer trends in the Sichuan Basin located in southwest China.This implies that the dynamical downscaling of RCM for long-term trends has certain seasonal and regional dependencies due to imperfect physical processes and parameterizations.  相似文献   

一种导航卫星中长期轨道预报方法     

周建华  杨龙  徐波  谢廷峰 《测绘学报》2011,(Z1)

基于神经网络混合建模的思想提出一种针对导航卫星的中长期轨道预报方法,在原动力学模型的基础上引入神经网络模型作为补偿,从而获得新的预报模型。在训练过程中神经网络通过学习动力学模型轨道预报误差来掌握其变化规律,并在预报过程中为动力学模型预报提供补偿,以提高预报精度。对GPS卫星动力学模型中长期预报误差的特点进行分析,然后根据所得结论提出混合模型的中长期(15 d以上)预报方案,最后通过对GPS卫星的仿真试验证明混合模型的改进效果,结果表明新方法在15~40 d的预报上表现出很好的改进效果。  相似文献   

基于DERF的SD方法预测月降水和极端降水日数   总被引：3，自引：1，他引：2       下载免费PDF全文

刘绿柳  孙林海  廖要明  杜良敏  李想 《应用气象学报》2011,22(1):77-85

针对动力气候模式对区域或更小空间尺度内的日降水预测技巧偏低的问题,应用最优子集回归 (OSR) 方法对国家气候中心业务化的月动力气候模式 (DERF) 输出的高度场、风场和海平面气压场进行降尺度处理用于降水预测,旨在提高预测准确率。1982—2006年交叉检验结果表明:OSR方法能显著提高降水预测技巧,其中11~40 d改善效果最为显著。在此基础上,应用一步法和两步法两种统计降尺度方法预测极端降水日数,交叉检验结果表明:两种方法均优于随机预测,冬季两步法预测技巧略高于一步法,夏季一步法略优于两步法。综合认为OSR,OSR结合随机天气发生器 (WG) 两种统计降尺度方法对月尺度降水或极端降水日数的预测均具有较高的技巧,可作为短期气候预测的重要参考信息。  相似文献   

统计降尺度方法在北京月尺度预测中的应用   总被引：1，自引：0，他引：1  

王冀  宋瑞艳  郭文利 《气象》2011,37(6):693-700

利用SDSM(statistical downscaling method)方法对北京47年(1961-2007年)的最低、最高气温和降水变化情况进行模拟评估,在此基础上对2008年北京奥运期间和2009年国庆期间天气变化进行实际预测应用。结果表明,SDSM方法具备模拟气温和降水等要素的能力。从年际变化模拟的情况上看,SDSM模型对气温模拟的效果好于降水,其中对于月平均最低(最高)气温模拟的效果好于最低(最高)气温极值的模拟。模型模拟的逐年极端最高(最低)气温结果在整体上偏低于实况气温,体现出气温极值模拟能力的不足。SDSM模型模拟的降水量整体上小于实测值,对降水极大值模拟能力更弱。对奥运会和国庆期间北京天气预测结果表明,模型对日最高、最低气温和降水的数值预测能力较差,预测值偏低于实际值,但升温和降温过程发生的时段能够准确的预测。  相似文献   

不同海域影响热带气旋强度变化的环境动力因素对比   总被引：1，自引：0，他引：1  

王喜  余锦华 《热带气象学报》2011,27(3):387-386

利用1982-2007年NCEP/NCAR再分析资料、月平均海平面温度(SST)资料和西北太平洋、北大西洋以及北印度洋热带气旋(TC)资料,对比分析了环境动力因素对不同海域TC强度在不同时间尺度变化的影响.结果表明,在各时间尺度上,TC强度变化与垂直风切变变化有密切的联系.在西北太平洋,使TC过程强度增强或减弱的风切变...  相似文献   

未来黄、东海营养盐浓度变化情景预测   总被引：1，自引：0，他引：1  

赵一丁  杨波  魏皓  赵亮 《海洋与湖沼》2015,46(5):983-994

本文基于FGOALS(Flexible Global Ocean-Atmosphere-Land System model)对未来气候情景的预测结果,结合千年生态评估的未来两个情景下的河流营养盐载荷特征,利用黄、东海水动力模型和生态模型并采用降尺度的方法对未来黄、东海营养盐的分布特征进行情景预测。结果表明,两个情景下未来河口邻近海区营养盐浓度将显著增加,富营养化加剧;GO(Global Orchestration)情景下,河流无机氮载荷增幅较大,夏季黄海中部无机氮浓度明显升高;AM(Adapting mosaic)情景下,由于河流无机磷载荷增幅较大,海区氮磷比有所下降,夏季黄海中部表层无机氮浓度降低,而在底层升高。通过敏感性实验并结合收支分析对各海区水动力条件未来变化、河流载荷变化的相对贡献进行了评估:相对于水温和水动力环境改变,河流营养盐排放量的增长是未来营养盐浓度增加的主要原因。营养盐收支分析表明,未来对流和混合输运的变化有助于黄海营养盐浓度的增加,夏季生物量升高造成更多碎屑沉降并在底层矿化使得层化季节冷水团底部营养盐浓度增长;长江口邻近海区营养盐浓度增长主要受冲淡水羽流的影响;净初级生产增加加剧了营养盐的消耗。  相似文献   

多源遥感数据的降水空间降尺度研究——以川渝地区为例   总被引：2，自引：0，他引：2  

嵇涛  刘睿  杨华  何太蓉  吴建峰 《地球信息科学学报》2015,(1):108-117

大量研究表明,通过传统地面气象站点实测的单点数据,不能有效地反映降水的空间变化特征。目前,以遥感数据获取的降水产品已得到了广泛的应用,但在地形地势复杂区域,遥感降水产品的空间分辨率与数据精度等方面仍然存在着极大的不足。因此,本文以四川重庆(川渝)地区为例,通过建立降水产品降尺度算法,以实现降水产品的降尺度估算,提高降水数据的空间分辨率。依据在不同尺度下(0.25°、0.50°、0.75°和1.00°),TRMM 3B43、地理因子,以及MOD13A3(NDVI)之间存在的相关关系,构建了多元回归模型。通过对比这4种尺度下的回归模型,选择其中精度最高的作为最终的降尺度算法,然后再把这种降尺度算法应用到1 km分辨率下进行降水估算。进一步,以区域差异分析(GDA)和区域比率分析法(GRA)对降尺度估算的降水数据进行校正,并结合部分地面气象站点实测的降水数据进行验证。验证结果表明:降尺度算法是可靠的,能有效提升降水产品的空间分辨率,同时GDA和GRA校正方法能减小误差,进一步提升降水估算的精度,满足区域地表过程应用的需求。  相似文献   

基于CCI和MODIS数据的淮河流域地表土壤湿度降尺度方法研究   总被引：1，自引：0，他引：1  

尤加俊  安如 《测绘与空间地理信息》2015,(2):30-34

土壤湿度是控制陆地和大气间水热能量交换的一个关键参数,同时也是陆面生态系统水循环的重要组成部分。本文选用25 km分辨率的CCI(Climate Change Initiative)土壤湿度产品数据,并结合1 km分辨率的MODIS数据,构建微波土壤湿度产品数据降尺度回归算法,获取淮河流域1 km空间分辨率的土壤湿度数据。降尺度后所获取淮河流域1 km空间分辨率的土壤湿度数据总体上提高了25 km空间分辨率的CCI土壤湿度产品数据的精度.  相似文献