中国区域陆面覆盖变化的气候效应模拟研究

基于MODIS和CLCV陆面覆盖资料,利用区域气候模式RegCM4分别进行两组24年（1978-2001年）的数值模拟试验,研究中国区域陆面覆盖变化对区域气候的影响。结果表明,以荒漠化和植被退化为主要特征的陆面覆盖变化通过改变陆面能量、水分平衡与大尺度环流进而对气候要素产生重要影响。夏季,中国南方地区普遍降温,季风边缘区及藏北高原气温升高,降水减少;季风边缘区与西北地区气温年际波动加剧;内蒙古中东部地区西南风增强,进而水汽输送增强,一定程度上增加了该地区降水。冬季,中国东部地区偏北气流增强,更多干燥冷空气南下,使得黄河以南地区降水减少、气温降低。     

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

使用区域气候模式RegCM4.4,对全球模式CSIRO-Mk3.6.0在RCP4.5情景下的气候变化试验结果（1950-2100年）在东亚地区进行25 km动力降尺度试验,比较了CSIRO-Mk3.6.0和RegCM4.4预估中国地区的21世纪气候变化。结果表明,两个模式预估未来中国地区气温持续升高,升温幅度具有区域性特征,RegCM4.4预估区域平均升温幅度低于CSIRO-Mk3.6.0,但二者年际波动基本一致。两个模式预估未来降水在中国西部以持续增加为主,东部则表现出较大的不一致性,预估区域平均年降水量变化不大,呈现冬季明显增加,夏季微弱减少的特点。此外,为了解区域气候模式对中国降水预估的不确定性,对本研究和以往RegCM3使用相同分辨率模拟得到的未来降水预估进行了对比,两个区域模式预估中国西部大部分地区未来降水一致性增加,东部存在明显不一致（冬季中、高纬除外）。     

中国东北地区气温变化的模拟评估与未来情景预估

基于RegCM4区域气候模式、CMIP5全球气候模式数据集和中国东北地区162个气象站气温观测资料,采用偏差分析和相关分析评估了RegCM4和CMIP5对东北地区气温的模拟能力,预估了RCP2.6、RCP4.5和RCP8.5排放情景下东北地区未来气温的变化.结果表明:区域模式和全球模式均能较好地再现气温时空变化特征,模...     

基于RegCM4模式的我国西南地区极端降水变化预估研究

基于5个全球气候系统模式结果驱动的高分辨率区域气候模式(RegCM4)模拟输出,系统评估了RegCM4模式对中国西南地区极端降水变化的模拟性能,并科学预估了中国西南地区极端降水的未来演变特征。结果表明,RegCM4模式能合理再现西南地区极端降水变化特征,但模拟的四川中部的湿偏差较大而四川盆地干偏差较大;进行偏差校正后,模拟性能有所提升,对西南地区极端降水模拟偏差有所减小。相较于当代气候(1986—2005年),就区域平均而言在21世纪(2021—2098年),有效降水总量(Prcptot)、强降水日数(R10 mm)、日最大降水量(Rx1day)和极端降水量(R95p)都明显增加;在RCP4.5和RCP8.5情景下,Rx1day和R95p在西南大部分地区增多,到21世纪末RCP4.5情景下增加幅度分别为16.0%和12.6%;Prcptot和R10 mm未来变化存在一定的区域差异,但Prcptot和R10 mm变化在空间上较为相似,在云南南部和四川盆地地区呈现减少趋势,其余地区增加明显;且RCP8.5高排放情景的变化幅度明显大于RCP4.5情景。     

RegCM3_IAP9L-AGCM对中国跨季度短期气候预测的回报试验研究

将区域气候模式RegCM3与中国科学院大气物理研究所全球大气环流模式IAP9L-AGCM进行单向嵌套,建立嵌套区域气候模式RegCM3_IAP9L-AGCM,并利用该嵌套模式对1982—2001年中国夏季短期气候进行了跨季度集合回报试验。结果表明,RegCM3_IAP9L-AGCM对高空气候变量(500hPa位势高度场、200和850hPa纬向风场)的回报结果与实况距平相关系数(ACC)基本为正,其回报效果好于单独使用IAP9L-AGCM的结果。除850hPa纬向风场外,其他两个变量场回报与实况正相关的区域基本呈纬向带状分布且通过90%信度检验。在中国大部分地区(除长江下游、东北北部和西北北部外),嵌套区域气候模式回报的降水距平百分率与实况基本为正相关。RegCM3_IAP9L-AGCM和IAP9L-AGCM对中国不同区域的夏季降水回报效果不同,前者对华南降水的回报效果明显好于后者。     

Aerosol Optical Properties Affected by a Strong Dust Storm over Central and Northern China

Aerosol observational data at 8 ground-based observation sites in the Chinese Sun Hazemeter Network(CSHNET)were analyzed to characterize the optical properties of aerosol particles during the strong dust storm of 16-21 April 2005.The observational aerosol optical depth(AOD)increased significantly during this dust storm at sites in Beijing city(86%),Beijing forest(84%),Xianghe(13%),Shapotou(27%),Shenyang(47%),Shanghai(23%),and Jiaozhou Bay(24%).The API(air pollution index)in Beijing and Tianjin also had a similar rise during the dust storm,while the Angstrm exponent(α)declined evidently at sites in Beijing city(21%),Beijing forest(39%),Xianghe(19%),Ordos(77%),Shapotou(50%),Shanghai(12%),and Jiaozhou Bay(21%),respectively.Furthermore,The observational AOD andαdemonstrated contrary trends during all storm stages(pre-dust storm,dust storm,and post-dust storm),with the AOD indicating an obvious"Valley-Peak-Valley"pattern of variation,whileαdemonstrated a"Peak-Valley-Peak"pattern. In addition,the dust module in a regional climate model(RegCM3)simulated the dust storm occurrence and track accurately and RegCM3 was able to basically simulate the trends in AOD.The simulation results for the North China stations were the best,and the simulation for dust-source stations was on the high side,while the simulation was on the low side for coastal sites.     

郑州市空气质量统计预报方法探讨

根据2005年、2006年采暖期RegCM 3模式输出产品和郑州市环境监测中心逐日监测资料,利用逐步回归方法建立了PM10、SO2、NO2等污染物质量浓度预报方程。该方法在2007年采暖期的试报中效果不理想,预报准确率明显低于历史拟合率。为了提高预报准确率,针对目前采用的统计方法中存在的不足,即在选择预报因子时没有考虑预报因子之间的相关性,挑选的预报因子由于非正交,使回归计算的结果不稳定。将自然正交分解和多元回归分析结合起来,以采暖期各污染物的日均质量浓度为预报对象,建立预报模型。结果表明,采用新方法制作的空气质量预报准确率有一定程度提高。     

Comparison of climate model results with European vegetation and permafrost during oxygen isotope stage three

Oxygen isotope stage 3 (OIS3), an interstade between approximately 60,000 and 25,000 yr B.P., presents an ideal opportunity to compare high-resolution climate simulations with the geologic record. To facilitate this comparison, the results of a mesoscale climate model (RegCM2) embedded in the GENESIS GCM are utilized to drive a vegetation model (BIOME 3.5). The BIOME output is then compared with OIS3 compilations derived from pollen. The simulated biomes agree well with the pollen-based biomes in southern Europe; however, disagreements occur in the northern part of the domain. The most striking mismatch involves the distribution of tundra. The models fail to have tundra extend to its observed position as far south as 50°N in central Europe during OIS3. The model also fails to have permafrost extend southward to its observed position between 50°N and 55°N in western Europe during OIS3. A variety of sensitivity experiments are performed to investigate these mismatches. These experiments demonstrate the importance of annual and summer temperatures and the length of the winter season in creating improved matches between the model results and the inferred distributions of vegetation and permafrost in northern Europe.     

European vegetation during Marine Oxygen Isotope Stage-3

European vegetation during representative “warm” and “cold” intervals of stage-3 was inferred from pollen analytical data. The inferred vegetation differs in character and spatial pattern from that of both fully glacial and fully interglacial conditions and exhibits contrasts between warm and cold intervals, consistent with other evidence for stage-3 palaeoenvironmental fluctuations. European vegetation thus appears to have been an integral component of millennial environmental fluctuations during stage-3; vegetation responded to this scale of environmental change and through feedback mechanisms may have had effects upon the environment. The pollen-inferred vegetation was compared with vegetation simulated using the BIOME 3.5 vegetation model for climatic conditions simulated using a regional climate model (RegCM2) nested within a coupled global climate and vegetation model (GENESIS-BIOME). Despite some discrepancies in detail, both approaches capture the principal features of the present vegetation of Europe. The simulated vegetation for stage-3 differs markedly from that inferred from pollen analytical data, implying substantial discrepancy between the simulated climate and that actually prevailing. Sensitivity analyses indicate that the simulated climate is too warm and probably has too short a winter season. These discrepancies may reflect incorrect specification of sea surface temperature or sea-ice conditions and may be exacerbated by vegetation-climate feedback in the coupled global model.     

月和季节尺度区域气候模拟的对比分析

利用区域气候模式RegCM3分别进行了东亚夏季月尺度和季节尺度区域气候模拟试验,并将两种时间尺度试验的逐月模拟结果进行了对比分析。结果表明,不同初始场和不同时间尺度模拟降水量存在一定的不确定性,但模拟的降水分布格局和模拟时间尺度关系不大,其模拟结果主要取决于模式对区域内大气降水过程的描述能力。两种时间尺度模拟的月平均环流形势几乎一致,随着模拟时间延长,两种时间尺度模拟的月平均环流、温度和湿度之间的差别在模式内部区域有所增加。但两者没有出现本质差别,且两者之间的偏差不会随模拟时间尺度的延长而无限制增长,只在一定范围内波动。两种时间尺度模拟对7月份淮河流域降水集中期暴雨和高低空急流刻画差别不大,但两者对8月份东北降水集中期模拟差别稍明显一些,其差别主要表现在对低空急流的模拟上。