乐清湾的动力沉积过程

主要采用二维潮波、泥沙输运途径的数值模拟，定量地展示了泥沙在乐清湾内的输运途径和沉降过程。模拟结果表明，乐清湾大致以10m等深线为界，其东部的涨潮流主要来自玉环岛与横趾山之间的深槽；水流在一周日内的轨迹为一宽约1km的狭带；此流态有利于泥沙向南的净输运，从面明利于此海域深水航道的维持。10m等深线以西水流轨迹为一较宽的带状结构，有利于泥沙向西、西北的净输运。华歧潮滩附近水流运动轨迹得于泥沙向北、向西的净输运，从而有利于华歧潮滩的发育。本文还定性讨论了楚门潮滩特征的成因,主要是漩门口堵截前丰富的湾外泥沙以及驻波型潮波与漏斗状地形。     

CCSD在线流体监测捕获的气体地球化学异常与2004年9．3级苏门答腊地震可能的超远程关系

中国大陆科学钻探工程在线流体地球化学监测在2004年12月10至2005年1月10日之间捕获到一段重要的气体地球化学异常。该异常从2004年12月24日晚上11点半开始到12月29日晚上7点半结束,其中在12月26日早上7点半到29日晚7点半这段异常非常特殊,表现出流体地球化学的剧烈变化。具体表现为流体组分从基本上不含Ar、He及N2跳跃到富含Ar、但亏损He和N2。该异常发生在2004年9.3级苏门答腊地震前1个半小时。由于CCSD现场离苏门答腊地震震中距离大于4170公里,大于该地震破裂长度1200公理的3倍,该地震在CCSD现场产生的静态应力变化微乎其微,不足以导致CCSD现场深部岩石或封闭破裂的岩石物理性质剧烈变化,因而可以排除静态激发效应的作用。在我国的云南和广东等地所观测到的地震异常和地下水位变化等表明2004年苏门答腊地震的动态激发效应主要沿东北方向,这和大地震的动态激发具有方向性一致。而CCSD现场就位于该方向上。我们推测2004年苏门答腊地震所产生的面波在CCSD现场激发的动态效应,导致库仑型失稳,增进深部岩石或破裂带的渗透率,释放富含Ar但亏损He和N2的流体,产生CCSD所观测到的气体异常。     

2001年春季中国北方沙尘暴的环流动力结构分析

通过对2001年春季中国北方5次沙尘暴的高度场，涡度场，散度场和风场的分析，研究了沙尘暴强盛期的环流动力结构。结果表明，在5次沙尘暴强盛期有相似的环流动力结构特征。在沙尘暴强盛期的高度场上，蒙古国有深厚的低值系统，乌拉尔高压发展，其间的强气压梯度是沙尘暴的动力源；低值系统有正涡度中心支持，外围是负涡度区，其间有强涡度梯度带；低值中心伴随有低层辐合高层辐散的垂直结构，易于发生近地面大风和上升气流，有利于地面起沙上扬，形成沙尘暴，大风区与强涡度梯度带一致，强风带切变形成的涡度输送有利于加强低值系统，进而增强风场。     

Assessing regression‐based statistical approaches for downscaling precipitation over North America

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.     

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada

We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973–1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10?km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.

Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX?>?25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45?km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability.     

国家级格点化定量降水预报系统

利用主客观融合降水反演、降水统计降尺度、降水时间拆分等技术构建了国家级格点化定量降水预报系统。该系统结构合理,模块功能明确,于2014年6月在国家气象中心投入业务使用,生成0~168 h时效,10 km分辨率,逐3 h的格点化定量降水预报产品。通过对2015年第13号热带气旋苏迪罗的格点化降水预报个例检验,结果显示,相比欧洲中期数值预报中心的确定性模式预报和预报员主观预报,该产品能更好地体现台风降水的时空精细化分布特点,对福建东北部和浙江东南部的特大暴雨中心位置表现更准确细致。通过对2015年4—9月的格点化产品整体效果检验,结果显示,相比欧洲中期数值预报中心的确定性模式预报和由反距离客观分析后的预报员主观预报,该产品既能保持和预报员主观预报相同的准确率,同时也能较明显地提高降水预报的时空精细化程度。     

月动力延伸预报500hPa高度场检验及其在重庆月气候预测中降尺度应用

根据2015年国家气候中心实时下发的第二代月动力延伸模式(DERF2.0)逐日资料和历史回算资料,统计构建不同时间起报的月500hPa高度场格点数据序列,针对重庆2月气温和8月降水量方差和预测难度较大的事实,分别分析2010-2014年逐年1月和7月16日、21日、26日、31日起报的2月和8月500hPa高度场预报场与同期NCEP资料实况场的分布型,结果表明：预测效果低纬好于中高纬,8月总体好于2月;基于上述滚动的500hPa预报场,试验了4个关键区和5种统计降尺度方法,对重庆2010-2015年2月气温和2010-2014年8月降水量进行回报预测和检验结果表明,16日起报的模式场对2月气温有较好的参考价值,配合最好的关键区为本区上空,而降尺度方案中Lamb方法效果最佳,二者结合的预测效果最好;8月降水回报检验表明,虽然8月降水预测效果不如2月气温,但在预测关键区取自定义关键区时,车氏方法的降尺度方案预测效果相对较好。     

中国地面气温统计降尺度预报方法研究

利用中国752个基本、基准地面气象观测站2000—2010年地面温度日值数据,采用具有自适应特征的Kalman滤波类型的递减平均统计降尺度技术,对中国地面温度进行精细化预报研究。分析该方案的降尺度效果,并与常用插值降尺度方法进行比较。结果表明:1)递减平均统计降尺度技术相比插值方法有较大的提高,显著减小东西部预报效果差异,1~3 d预报的均方根误差减小了1.4℃;2)该方案1~3 d预报的均方根误差为1.5℃,预报误差从东南地区(均方根误差为1.4℃)向西北地区(均方根误差为1.8℃)逐渐增大,并且预报效果夏季优于冬季。因此,递减平均统计降尺度技术对中国地面温度进行精细化预报是可行的。     

结合像元分解和STARFM模型的遥感数据融合

高空间、时间分辨率遥感数据在监测地表快速变化方面具有重要的作用。然而,对于特定传感器获取的遥感影像在空间分辨率和时间分辨率上存在不可调和的矛盾,遥感数据时空融合技术是解决这一矛盾的有效方法。本文利用像元分解降尺方法(Downscaling mixed pixel)和STARFM模型(Spatial and Temporal Adaptive Reflectance Fusion Model)相结合的CDSTARFM算法(Combination of Downscaling Mixed Pixel Algorithm and Spatial and Temporal Adaptive Reflectance Fusion Model)进行遥感数据融合。首先,利用像元分解降尺度方法对参与融合的MODIS数据进行分解降尺度处理;其次,利用分解降尺度的MODIS数据替代STARFM模型中直接重采样的MODIS数据进行数据融合;最后以Landsat 8和MODIS遥感影像数据对该方法进行了实验。结果表明:(1)CDSTARFM算法比STARFM和像元分解降尺度算法具有更高的融合精度;(2)CDSTARFM能够在较小的窗口下获得更高的融合精度,在相同的窗口下其融合精度也高于STARFM;(3)CDSTARFM融合的影像更接近真实影像,消除了像元分解降尺度影像中的"图斑"和STARFM模型融合影像中的"MODIS像元边界"。     

基于CWRF的中国近海热带气旋集合模拟及其对物理参数化方案的敏感性研究

为评估CWRF模式的降尺度能力和其热带气旋模拟对物理参数化方案的敏感性,本文利用ERI再分析资料驱动CWRF在30km网格上对1982-2016年中国近海热带气旋开展了一次集合模拟.结果表明:CWRF与ERI均能模拟出热带气旋的季节变化和年际变化形势且均存在低估,但相较ERI,CWRF的降尺度技术和集合模拟可以再现更多的热带气旋,显著减少低估.年际变化结果提升最为明显,它对积云方案最为敏感,其次是边界层,陆面和辐射方案,对云和微物理方案较弱.该研究为应用CWRF理解和预报热带气旋提供了参考.