The relative influence of climate and housing development on current and projected future fire patterns and structure loss across three California landscapes

Climate and land use patterns are expected to change dramatically in the coming century, raising concern about their effects on wildfire patterns and subsequent impacts to human communities. The relative influence of climate versus land use on fires and their impacts, however, remains unclear, particularly given the substantial geographical variability in fire-prone places like California. We developed a modeling framework to compare the importance of climatic and human variables for explaining fire patterns and structure loss for three diverse California landscapes, then projected future large fire and structure loss probability under two different climate (hot-dry or warm-wet) and two different land use (rural or urban residential growth) scenarios. The relative importance of climate and housing pattern varied across regions and according to fire size or whether the model was for large fires or structure loss. The differing strengths of these relationships, in addition to differences in the nature and magnitude of projected climate or land use change, dictated the extent to which large fires or structure loss were projected to change in the future. Despite this variability, housing and human infrastructure were consistently more responsible for explaining fire ignitions and structure loss probability, whereas climate, topography, and fuel variables were more important for explaining large fire patterns. For all study areas, most structure loss occurred in areas with low housing density (from 0.08 to 2.01 units/ha), and expansion of rural residential land use increased structure loss probability in the future. Regardless of future climate scenario, large fire probability was only projected to increase in the northern and interior parts of the state, whereas climate change had no projected impact on fire probability in southern California. Given the variation in fire-climate relationships and land use effects, policy and management decision-making should be customized for specific geographical regions.     

多因子和多尺度合成中国夏季降水预测模型及预报试验

根据青藏高原60个站平均的月积雪深度、热带太平洋Nino 3区月海温和中国160个站月降水量等资料,用小波变换和相关分析,分析了1958～1998年秋冬季青藏高原异常雪盖与El Nino-南方涛动(ENSO)的关系、多时间尺度变化的特征及其与中国夏季降水的相关型式.并取青藏高原积雪和Nino 3区海温的年际变化、年代际变化和线性趋势三种不同时间尺度的小波分量作为预报因子,对我国夏季降水距平作线性回归,建立了相应的预测模型.最后,利用1999～2002年的独立资料进行了预报试验,并在2003年和2004年应用于实际预报.研究表明,青藏高原雪盖与ENSO这两个物理因子彼此具有一定的独立性.它们都是多时间尺度现象,并与中国夏季降水有较好的关系.在不同时间尺度上不仅有不同的相关型式,而且相对贡献也有变化.回归预测模型的拟合情况和预报试验表明,综合考虑前期秋冬季青藏高原雪盖和ENSO这两个物理因子的年际变化、年代际变化和线性趋势作为预报因子建立的预测我国夏季降水距平分布的模型,有一定的预报能力.     

SOME ASPECTS OF THE INTERACTION OF BLOWING SNOW WITH THE ATMOSPHERIC BOUNDARY LAYER

Several possible effects of blowing snow on the atmospheric boundary layer are investigated, mostly within the general framework of the Prairie Blowing Snow Model (PBSM). The processes of snow saltation and suspension are first described. Variations to the drift density profile are tested and the effects of stratification and density variation calculations are evaluated. Despite high density gradients of blowing snow, stratification effects on turbulence and the velocity profiles can generally be neglected. However, with saltating or suspended snow in a constant shear stress layer, part of the shear stress is carried by the particles. A highly simplified, single-phase approach, based on the density variation of the air–snow mixture coupled to a simple turbulent stress–strain relationship, is used to illustrate this. Sublimation rates in a column of blowing snow are calculated using the PBSM and results are compared with those obtained with a modified formulation which incorporates a spectrum of sublimating particles of varying sizes at each height in a steady-state surface boundary layer and different specifications of the ventilation velocity.     

SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.     

欧亚春季雪盖对印度洋偶极子的影响

文章研究了欧亚春季雪盖对印度洋偶极子的影响。研究发现,欧亚春季雪盖与印度洋偶极子关系密切,两者之间存在显著的反相关关系。欧亚春季雪盖异常导致夏季赤道印度洋垂直纬向环流以及印度洋和欧亚大陆之间的垂直经向环流发生异常,是欧亚春季雪盖与印度洋偶极子存在反相关关系的主要原因。欧亚春季雪盖异常可能是印度洋偶极子发生的一个重要的外在诱发因子。     

磁化率和密度对中国大陆科学钻探主孔100～2000 m岩石类型的判别

为查明磁化率和密度对于中国大陆科学钻探工程(CCSD)主孔100~2000m岩性的响应和判别特征,利用SPSS10.0统计分析软件进行了判别分析.研究结果显示,岩石的密度和体积磁化率主要受岩性的控制.采用迫入法建立全模型,对CCSD主孔100~2000m井段岩心的岩性判别率达84.8%.其中,蛇纹石化橄榄岩、正片麻岩、副片麻岩、榴辉岩、角闪岩和退变质榴辉岩的判别率分别为100%、87.1%、89.7%、89.6%、96.7%和63.7%.该研究表明,密度和磁化率可以为超高压变质岩石的岩性鉴别和区分提供定量约束,有利于地球物理探测成果和测井资料的准确解析.同时,本文也是SPSS统计分析软件在超高压变质岩石类型判别方面的一个应用实例,对于其他岩石类型的判别分析具有借鉴意义.     

城市人口分布空间自相关的功率谱分析

从理论上可以证明标准的城市人口密度负指数距离衰减模型本质上是一种空间相关函数,基于这种思想对Clark模型进行Fourier变换,可以导出城市人口密度的幂次频谱分布,且功率谱指数理应为β=2±。负指数与幂指数的这种变换关系暗示了城市地理系统简单与复杂的辩证关系。借助中国杭州市4年的人口普查资料转换的平均人口密度分布数据对上述推论进行检验,发现β渐进式趋近于2但并不约等于2。将β值进一步换算为人口过程的分维D和Hurst指数H,结果表明：城市人口具有长程负相关作用,但这种空间作用显示明确的局域化倾向。目前的城市形态演化模拟几乎无一例外地引入了长程作用,根据杭州人口分布的局域化特征,有关地理长程作用的假设和应用有必要重新探讨。     

印度洋9.0级大地震激发的地球球型振荡和环型振荡

综合分析了中国数字地震台网（CDSN）改造后的5个长周期地震仪台站观测的3天的VHZ、VHE和VHN波形资料,利用功率谱密度估计方法,在没有对资料进行去固体潮处理的情况下,准确获得了2004年12月26日印度洋地震激发的0S3~0S78的基频球型振荡和部分谐频球型振荡和0T3~0T67的基频环型振荡,并与地球初步参考模型（PREM）的理论自由振荡周期进行了对比,发现实测振荡周期与PREM预测的振荡周期符合的很好.频率与PREM模型略微不一致的球型或环型振荡可以解释为地球介质的横向不均匀性和各向异性所致.因此地球自由振荡信息可用于揭示地球的三维不均匀结构信息或各向异性信息,并可能对区分地幔对流模式有所帮助.     

高层大气密度的午夜极大值特征分析与建模

利用CHAMP (CHAllenging Minisatellite Payload)、GRACE-A (Gravity Recovery and Climate Experiment-A)、SWARM-C (The Earth''s Magnetic Field and Environment Explorers-C)等3颗极轨卫星的资料, 研究360—480km高层大气密度在低纬度区域的午夜极大值(Midnight Density Maximum, MDM)现象. MDM一般出现在23:00- 02:00 LT (Local Time)之间,峰值位置在低纬度15°以内,谷值位置在中纬度35°-45°附近,整体略偏向南半球,振幅约为平均密度的26%.随着高度增大以及太阳辐射水平的增强,MDM振幅呈减小趋势;冬至和夏至日附近的季节效应会减弱MDM振幅,在春秋分日的振幅最大.用3个主流大气模型DTM2000 (Drag Temperature Model 2000), NRLMSISE00 (US Naval Research Laboratory, Mass Spectrom-eter and Incoherent Scatter radar)和JB2008 (Jacchia- Bowman 2008 model)对MDM进行模拟,JB2008没有刻画出MDM现象;另两个模型低估了MDM效应,在360km和480km两个高度DTM2000模型的振幅仅为观测的46%和53%, NRLMSISE00模型仅为观测的33%和26%;模型没有准确刻画出MDM与高度、辐射水平和季节的关系.联合3颗卫星的资料,研究了-种基于地理纬度的6阶勒让德多项式,同时融合地方时和高度因素的经验函数,在振幅和相位上可以较好地刻画MDM特征,相关系数达到0.923,可为大气密度模型的修正提供借鉴,服务于低轨道航天器高精度轨道预报.