高原东部地区一次雹云成雹过程的数值模拟

本文利用一维半时变双参数积云模式，对高原东部地区一次西风槽影响下的冰雹天气过程进行了数值模拟。讨论了该雹云内的动力、热力特点以及过冷云滴、冰晶、霰、雹的产生和转化以及降水粒子碰并增长等物理过程。对高原雹云的成雹机制作了初步探讨     

相关法雷达反演风场在台风监测和分析中的应用

随着我国沿海雷达网的建设,雷达资料正逐步成为沿海气象台站台风临近登陆时的一个重要监测手段。利用相关法雷达风场反演对2001年登陆台风“百合”和“飞燕”作了环流和强度估测分析。结果表明,通过适当的质量控制,该方法可以有效地反演得到台风强风分布特征,分析精度与业务中常用的卫星估测方法相当。     

山东半岛冷流降雪过程的统计分析

对威海地区2001-2006年1、2、11、12月所有冷流过程的温压湿等气象要素进行分析,结果表明:地面偏西北风有利于冷流过程的发生;冷流降水量与海气温差有着较强的正对应关系,而与大气相对湿度没有明显的对应关系.相关系数进一步表明了850 hPa温度与海温之差直接决定了地面冷流降水量的大小.从探空指教和垂直湿位涡分布可以看出.,管大气近于弱的对流稳定,但仍不影响对称不稳定的产生.     

哈尔滨气温变化特征分析

上世纪80年代以来,哈尔滨年平均气温明显上升,在127年中上升了2.7℃。主要冬季升幅最大,春季次之,再次为秋季,夏季升幅最小。平均最低气温的升幅较明显,远高于平均最高气温的升幅,冬季最低气温的升幅最大夏季的升幅次于春季;秋季升幅最小。另外还分析了气温年代际变化特征。     

气象卫星接收天线标校技术及应用

在过去的几十年中,我国气象事业的不断发展,中国风云气象卫星完成了从试验应用型向业务服务性的不断转型,因此对于卫星信号接收天线的可靠性和指向精度要求越来越高。目前用于接收风云系列极轨气象卫星下行信号的天线主要有12m和4.2m天线,其具有动态特性高、波束宽度窄等特点,因此需要在天线安装和运行期间对天线的轴系误差进行精确的标定和校准。本文在传统标校方法的基础上,提出了利用太阳进行的误差标校技术,进一步降低了标校环节的复杂程度,提高了标校精度。     

Surface energy, water and carbon cycle in China simulated by the Australian community land surface model (CABLE)

Through an Australia-China climate change bilateral project, we analyzed results of 51-year global offline simulations over China using the Australian community atmosphere biosphere land exchange (CABLE) model, focusing on integrated studies of its surface energy, water and carbon cycle at seasonal, interannual and longer time-scales. In addition to the similar features in surface climatology between the CABLE simulation and those derived from the global land-surface data assimilation system, comparison of surface fluxes at a CEOP reference site in northeast China also suggested that the seasonal cycles of surface evaporation and CO₂ flux are reasonably simulated by the model. We further assessed temporal variations of model soil moisture with the observed variations at a number of locations in China. Observations show a soil moisture recharge–discharge mechanism on a seasonal time scale in central-east China, with soil moisture being recharged during its summer wet season, retained in its winter due to low evaporation demand, and depleted during early spring when the land warms up. Such a seasonal cycle is shown at both 50- and 100-cm soil depths in observations while the model only shows a similar feature in its lower soil layers with its upper layer soil moisture varying tightly with rainfall seasonal cycle. In the analysis of the model carbon cycle, the net primary productivity (NPP) has similar spatial patterns as the ones derived from an ecosystem model with remote sensing. The simulated interannual variations of NPP by CABLE are consistent with the results derived from remote sensing-based and process-based studies over the period of 1981–2000. Nevertheless an upward trend from observations is not presented in the model results. The model shows a downward trend primarily due to the constant CO₂ concentration used in the experiment and a large increase of autotrophic respiration caused by an upward trend in surface temperature forcing data. Furthermore, we have compared river discharge data from the model experiments with observations in the Yangtze and Yellow River basins in China. In the Yangtze River basin, while the observed interannual variability is reasonably captured, the model significantly underestimates its river discharge, which is consist with its overestimation of evaporation in the region. In the Yellow River basin, the magnitudes of the river discharge is similar between modeled and observed but its variations are less skillfully captured as seen in the Yangtze River region.     

A comparison of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assessments

Spatial downscaling of climate change scenarios can be a significant source of uncertainty in simulating climatic impacts on soil erosion, hydrology, and crop production. The objective of this study is to compare responses of simulated soil erosion, surface hydrology, and wheat and maize yields to two (implicit and explicit) spatial downscaling methods used to downscale the A2a, B2a, and GGa1 climate change scenarios projected by the Hadley Centre’s global climate model (HadCM3). The explicit method, in contrast to the implicit method, explicitly considers spatial differences of climate scenarios and variability during downscaling. Monthly projections of precipitation and temperature during 1950–2039 were used in the implicit and explicit spatial downscaling. A stochastic weather generator (CLIGEN) was then used to disaggregate monthly values to daily weather series following the spatial downscaling. The Water Erosion Prediction Project (WEPP) model was run for a wheat–wheat–maize rotation under conventional tillage at the 8.7 and 17.6% slopes in southern Loess Plateau of China. Both explicit and implicit methods projected general increases in annual precipitation and temperature during 2010–2039 at the Changwu station. However, relative climate changes downscaled by the explicit method, as compared to the implicit method, appeared more dynamic or variable. Consequently, the responses to climate change, simulated with the explicit method, seemed more dynamic and sensitive. For a 1% increase in precipitation, percent increases in average annual runoff (soil loss) were 3–6 (4–10) times greater with the explicit method than those with the implicit method. Differences in grain yield were also found between the two methods. These contrasting results between the two methods indicate that spatial downscaling of climate change scenarios can be a significant source of uncertainty, and further underscore the importance of proper spatial treatments of climate change scenarios, and especially climate variability, prior to impact simulation. The implicit method, which applies aggregated climate changes at the GCM grid scale directly to a target station, is more appropriate for simulating a first-order regional response of nature resources to climate change. But for the site-specific impact assessments, especially for entities that are heavily influenced by local conditions such as soil loss and crop yield, the explicit method must be used.     

汉江流域极端水文事件时空分布特征

利用1960-2012年汉江流域15个气象站点的日降雨资料和3个水文站同时期日径流资料,分析了9个极端降雨指数的空间分布规律,运用广义极值分布（GEV）、Gamma分布两种极值统计模型对各站点的最大1 d降雨、最大3 d降雨极值样本进行拟合,遴选描述降雨极值分布规律最优概率模型,进而推算给定重现期下的降雨设计值,并分析其空间分布规律;选用Gumbel、Clayton和Frank这3种Copula函数建立降雨-洪量极值联合分布模型,优选最合适的Copula函数,由此计算给定重现期下的洪量设计值。结果表明：GEV分布模型能更好地模拟降雨极值序列,不同重现期下的降雨极值在空间上均呈西低东高的特征;3种Copula函数中,Frank Copula函数能更好地拟合降雨-洪量相关关系,由此推求的洪量设计值大于单变量拟合设计值。