生态地理学概念界定及其经典案例分析

对生态地理学的概念进行了详细讨论和辨析,并将它与相近学科如生物地理学、生态地理区划、宏生态学等进行了比较分析,界定了生态地理学的概念。研究认为：生态地理学是生态学和地理学的交叉学科,是研究生态系统各组分关系和生态过程的地理空间分布格局或/和时间演变规律及其与地理环境耦合机制的学科。生态地理学的目的是揭示不同环境梯度下或不同时间尺度上生态系统各组分关系和生态过程的普适性规律及其成因。同时,结合国内外野外实验平台介绍,在全球变化等研究领域列举了经典案例进行分析：① 全球不同气候带森林凋落物分解和碳汇功能的研究;② 中国不同陆地生态系统碳通量和碳汇功能研究;③ 中国东北样带和南北样带陆地生态系统的脆弱性与适应性研究;④ 中国北方草地样带尺度的生态系统生态学研究。主要目的是在辨析生态地理学概念的基础上指出未来发展方向,推动生态地理学的发展。     

基本气流的垂直切变作用下的低纬低频波

在低纬地区,风速的垂直切变也是很明显的,作者解释了这些纬向气流的垂直切变对低纬长波性质以及对不同模态的相互作用的影响,并且发现切变对低纬波动的影响具有明显的选择性.     

工业SO2排放对东亚和我国温度变化的影响

根据东亚地区工业ＳＯ２排放资料和硫化物输送模式模拟得到的ＳＯ２－４气溶胶的区域分布状况,计算了ＳＯ２－４对地气系统的直接辐射强迫作用,并用能量平衡模式模拟了其对东亚和我国温度变化的影响。模拟结果和资料分析表明,８０年代以来在全球变暖的背景下,我国南方大部分地区平均气温（特别是日最高温度和白天温度）普遍下降。工业ＳＯ２排放引起的大气中ＳＯ２－４含量的增加可能是引起降温的主要原因之一     

山地蒸发的计算

本文研讨了山地下垫面蒸发的计算，提出了根据迳流系数和降水强度确定计算蒸发公式中与地形、植被、土壤等下垫面特性降水性质有关的参数的方法，经实际检验，结果令人满意。     

石家庄市采暖期气象服务系统

在采暖期内为了做到既能让人们感到冷暖适宜，又能合理地减少采暖期内的采暖能源浪费，该文对石家庄市采暖期气象条件进行了详细分析，建立了与气象预报相结合的采暖气象服务系统，实际应用效果良好。     

中—β尺度强对流风暴和暴雨数值模拟中的一些问题

本文利用数值模拟方法探讨各环境背景因子对强对流及暴雨系统发生发展所起的作用，分析了暴雨和强对流风暴的形成机制。结果表明：温度场和湿度场的垂直分布，决定着对流是否可以形成；其水平非均匀性只是改变风暴发展强度、生命期以及分裂特性。风场的动力影响对强风暴的移动、分裂及强度特征也十分重要。最后，对第三运动方程做了量纲分析，发现热浮力是对流风暴发展的决定性因素；而热浮力冲量能更细致地反映对流风暴的发展演变特征。     

乾安地区盐碱地显热通量的测量

文中给出了用大孔径闪烁仪在 2 0 0 0年生长季观测到的盐碱地区显热通量的主要结果 ,并初步计算了当地的水热平衡状况。结果表明 :乾安盐碱地区显热通量占净辐射量的百分比在干旱、非生长季达到 6 5 % ,在多雨、植被生长季仅为 11% ;显热通量因降水而明显降低 ,幅度与降水强度有关 ,反映了当地的气候和土壤特征。文中还把LAS的测量结果与传统的梯度法作了比较 ,结果基本一致。     

Assessing vegetation dynamics and their relationships with climatic variability in Heilongjiang province, northeast China

In this study, the vegetation dynamics in Heilongjiang province and their relationships with climate variability were assessed using normalized difference vegetation index (NDVI) and meteorological datasets from 1981 to 2003. The conclusions from our results are as follows: (1) After 1981, vegetation cover, as indicated by the NDVI, exhibited an insignificant increasing tendency. However, the inter-annual variations of the NDVI showed apparent spatial differentiations. (2) The inter-annual changes of the NDVI were different from season to season. The spring and autumn NDVI values increased, while the summer and winter NDVI decreased. (3) The annual NDVI was significantly correlated with precipitation. Thus, as compared to temperature, precipitation was the dominant climatic factor affecting the vegetation dynamics in Heilongjiang province. (4) The trend in the NDVI showed a marked homogeneity corresponding to regional and seasonal variations in climate. Additionally, land use changes also play an important role in influencing the NDVI trends over some regions. All of these findings will enrich our knowledge of the natural forces that impact the stability of boreal ecosystems and provide a scientific basis for the environmental management in Heilongjiang province in response to climate change and human activities.     

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960–2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001–2010) and the predicting period (2011–2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.     

Impact of Cloud Microphysical Processes on the Simulation of Typhoon Rananim near Shore. Part II: Typhoon Intensity and Track

The impact of cloud microphysical processes on the simulated intensity and track of Typhoon Rananim is discussed and analyzed in the second part of this study. The results indicate that when the cooling effect due to evaporation of rain water is excluded, the simulated 36-h maximum surface wind speed of Typhoon Rananim is about 7 m s⁻¹ greater than that from all other experiments; however, the typhoon landfall location has the biggest bias of about 150 km against the control experiment. The simulated strong outer rainbands and the vertical shear of the environmental flow are unfavorable for the deepening and maintenance of the typhoon and result in its intensity loss near the landfall. It is the cloud microphysical processes that strengthen and create the outer spiral rainbands, which then increase the local convergence away from the typhoon center and prevent more moisture and energy transport to the inner core of the typhoon. The developed outer rainbands are supposed to bring dry and cold air mass from the middle troposphere to the planetary boundary layer (PBL). The other branch of the cold airflow comes from the evaporation of rain water itself in the PBL while the droplets are falling. Thus, the cut-off of the warm and moist air to the inner core and the invasion of cold and dry air to the eyewall region are expected to bring about the intensity reduction of the modeled typhoon. Therefore, the deepening and maintenance of Typhoon Rananim during its landing are better simulated through the reduction of these two kinds of model errors.