沙尘输送模式的不确定性分析

利用一个远距离输送的沙尘模式估计了由于参数化过程 (干沉降速度) 和输入资料 (源强和水平风场) 的误差造成沙尘模拟的不确定性。通过对以上参数分别进行敏感性试验, 分析了模式对2002年3月15～24日期间中国东部地区两次主要沙尘过程模拟的不确定性。结果显示, 源区的潜在源强和气象水平风场的不确定性对模拟结果的影响最大, 而干沉降速度的影响相对较小。同时, 对不同区域 ［西部 (＜95°E)、中部 (95°E～110°E) 和东部 (＞110°E)］ 的潜在源强和干沉降速度参数进行敏感性试验发现, 中部区域的参数设置对模拟结果的影响最大, 而西部和东部区域的参数变化对模拟结果的影响很小。此外, 不同高度的风场影响也不一样: 地面风速影响最大, 中层的影响较小, 而高层 (约6 km高度以上) 的风场几乎没有影响。     

模糊优选神经网络模型在城市防洪规划方案优选中的应用

城市防洪规划方案的综合优选是一个涉及到政治、社会、经济、环境等多准则、多因素的复杂多目标决策问题.针对目前各种常用的综合优选模型应用中存在的指标权重选择及转换问题,利用模糊优选神经网络模型,构造了合理的网络拓扑结构并将模型应用于某城市的防洪规划方案综合优选中.实例结果表明,此模型不仅避免了对指标权重的处理问题,而且明显加快了BP网络的收敛速度.     

两类不同月平均气温空间推算方法的对比

利用全国660个常规气象站40年(1961-2000年)整编气象资料.采用逆距离权重反比法、样条函数法和普通克立格法等常用的3种插值方法,分析了直接插值法和综合余项法对气温插值的影响,提出了去除气温形成中的确定性部分后,以随机项进行插值可提高气温插值精度。并从空间上、时间上对比眲不同插值方法的误差,最后分析了气象站的空间分布密度对插值方法的敏感性。验证结果表明:除个别月份外,综合余项法的各项平均绝对误差均在1℃以内,比直接插值法减小了0.6～1.6℃,精度提高了38%～85%;且综合余项法的精度不依赖于台站密度的大小、插值方法的不同,具有较高的精确性和稳定性,这说明影响空间插值精度的关键因子并非是气象观测站点密度的提高、空问插值方法的改进。     

降水性层云含水量跃变对应的微结构观测研究

利用长春2007年5月16日的一次层状云降水过程的飞机观测资料,并结合天气图、卫星云图及雷达回波等资料,综合分析了此次降水过程中粒子浓度、粒子谱、雷达垂直累积液态水（vertical integrated liquidwater,VIL）、微波辐射计积分液态水（liquid water content,LWC）以及地面雨强特征。研究表明,层状云微结构在水平方向上的起伏较大,出现两次典型的含水量跃变：第1次液态水跃变主要是因为粒子浓度增加;第2次液态水跃变是因为粒子浓度和粒子谱共同作用的结果;雷达VIL值和地面雨强两者呈正相关。     

自然湿地甲烷排放模拟研究——模型的灵敏度分析与应用

对甲烷湿地排放模型CH4MODwetland进行灵敏度分析表明,环境驱动因素——温度和地表水深是影响甲烷排放通量的主要因素,地表水深对季节性积水沼泽甲烷排放通量的灵敏度大于常年积水沼泽。模型对植物和土壤输入参数的灵敏度响应依次为Wmax(地上生物量最大值)FR(地下净初级生产力占植物总净初级生产力的比例)fV(植被类型系数)TAmax(植物从生长初期到最大地上生物量所需有效积温)ρ(容量),OM(土壤有积质含量)SAND(土壤砂粒含量)。以经验水位模型驱动CH4MODwetland,模拟三江平原毛果苔草和小叶章沼泽(1950年代～2000年代),以及若尔盖高原木里苔草和乌拉苔草沼泽(1960年代～2000年代)多年甲烷排放通量的变化。结果表明,年代际甲烷排放通量的变化主要受降水量的影响,但气候变暖使得降水量基本相同的年代甲烷排放通量增加:三江平原毛果苔草沼泽和小叶章沼泽(1980年代～2000年代比1950年代～1970年代模拟的甲烷排放通量分别增加了9.5%和8.3%;若尔盖高原乌拉苔草沼泽和木里苔草沼泽(1990年代～2000年代比1960年代～1970年代)分别增加了6.0%和5.5%。该结论能够为评估未来气候变化对中国湿地甲烷排放的影响提供依据。     

青藏高原积雪日数的气温敏感度分析

根据青藏高原气象台站观测积雪日数和均一化气温数据,对高原1951—2004年积雪日数对气温的敏感度进行了量化分析。研究表明,无论是极值敏感度还是当前气候下的敏感度,空间上都呈现出高原四周积雪较中部对气温的敏感程度高的情况。各台站积雪日数对气温最敏感时的临界气温与海拔有着极好的反相关关系,而极值敏感度与海拔虽然也有一定的反相关,但相关程度远不如前者高。在当前气候状态下,有相当一部分台站的平均气温还未达到临界值,这些台站在秋、冬、春、夏季分别占总台站数的36%、39%、47%和11%。未来气候继续变暖背景下,这部分台站积雪日数对气温的敏感度会进一步加大,即积雪对气温的升高会更加敏感。     

RIEMS2.0不同模拟区域模拟中国北方多年气候平均态比较

Regional Integrated Environment Modeling System Version 2.0 （RIEMS2.0） is now being developed by the Key Laboratory of Regional Climate-Environment for Temperate East Asia, Chinese Academy of Sciences. In order to test the sensitivity of the RIEMS2.0 model domain to simulate long-term climate and its change, and provide a basis for the further development and application of the model, the authors compared results between simulated and observed precipitation and surface-airtemperature using two model domains under different cumulus parameterization schemes. The model was driven by NCEP/NCAR re-analysis data with a simulation duration ranging from 1 January 1979 to 31 December 2007. There were no significant differences found in the spatial distributions of the simulated precipitation and surface-air-temperature, or interannual variations between the two model domains. There were, however, differences observed between the two model domain simulations of local sub-regions. The smaller model domain more accurately simulated precipitation, especially in summer （June, July, and August）, and decreased the bias of surface-airtemperature, especially in winter （December, January, and February）. The weak summer and winter monsoons simulated by the smaller model domain was a result of boundary forcings and may partially account for the improvements of this model.     

Sensitivity of Nonlinearity on the ENSO Cycle in a Simple Air-sea Coupled Model

In this paper,the influence of the El NioSouthern Oscillation (ENSO) cycle on the sensitivity of nonlinear factors in the numerical simulation is investigated by conducting numerical experiments in a simple air-sea coupled model for ENSO prediction.Two sets of experiments are conducted in which zonal nonlinear factors,meridional nonlinear factors,or both are incorporated into the governing equations for the atmosphere or ocean.The results suggest that the ENSO cycle is very sensitive to the nonlinear factor of the governing equation for the atmosphere or ocean.Thus,incorporating nonlinearity into air-sea coupled models is of exclusive importance for improving ENSO simulation.     

Forecasting the western Pacific subtropical high index during typhoon activity using a hybrid deep learning model

Seasonal location and intensity changes in the western Pacific subtropical high(WPSH) are important factors dominating the synoptic weather and the distribution and magnitude of precipitation in the rain belt over East Asia. Therefore, this article delves into the forecast of the western Pacific subtropical high index during typhoon activity by adopting a hybrid deep learning model. Firstly, the predictors, which are the inputs of the model, are analysed based on three characteristics: the first...     

The Late Miocene climate response to a modern Sahara desert

The climate cooling and vegetation changes in the Miocene/Pliocene are generally well documented by various proxy data. Some important ecosystem changes occurred at that time. Palaeobotanical evidence suggests that the Sahara desert first appeared in the Pliocene, whereas in the Miocene North Africa was green. In the present study, we investigate the Late Miocene climate response to the appearance of the Sahara desert from a climate modelling sensitivity experiment. We compare a model experiment, which includes a full set of Late Miocene boundary conditions, with another one using the same boundary conditions except that the North African vegetation refers to the present-day situation. Our sensitivity study demonstrates that the introduction of the Sahara desert leads to a cooling and an aridification in Africa. In addition, we observe teleconnection patterns related to the North African desertification at around the Miocene/Pliocene boundary. From our sensitivity experiment, we observe that the Sahara contributes to a cooling in Central Asia and in North America. As compared to hypsodonty data for Central Asia, an increased aridity is underestimated in the Sahara experiment. Finally, we observe that the introduction of the Sahara leads to a cooling in the northern high latitudes. Hence, our sensitivity experiment indicates that the appearance of the Sahara desert is one piece to better understand Late Cenozoic climate cooling being most pronounced in the high latitudes.