Effect of parallel electric field on electrostatic ion-cyclotron instability in anisotropic plasma in the presence of ion beam and general distribution function—Particle aspect analysis

Dispersion relation, resonant energy transferred, growth rate and marginal instability criteria for the electrostatic ion-cyclotron wave with general loss-cone distribution in low-β anisotropic, homogeneous plasma in the auroral acceleration region are discussed by investigating the trajectories of the charged particles. Effects of the parallel electric field, ion beam velocity, steepness of the loss-cone distribution and temperature anisotropy on resonant energy transferred and growth rate of the instability are discussed. It is found that the effect of the parallel electric field is to stabilize the wave and enhance the transverse acceleration of ions whereas the effect of steepness of loss-cone, ion beam velocity and the temperature anisotropy is to enhance the growth rate and decrease the transverse acceleration of ions. The steepness of the loss-cone also introduces a peak in the growth rate which shifts towards the lower side of the perpendicular wave number with the increasing steepness of the loss-cone.     

中国最高、最低温度及日较差在海拔高度上变化的初步分析

本文利用中国740个气象台站1963~2012年均一化逐日最高温度和最低温度资料,分析了中国地区最高、最低气温和日较差变化趋势的区域特征及其与海拔高度的关系。结果表明:近50年气温的变化趋势无论是年或季节变化,最低温度的增温幅度都高于最高温度,且其增温显著区域都对应我国高海拔地区。除了春季,其他季节最高、最低温度及日较差的升温幅度随着海拔高度的升高而增大,其中最高温度的变化趋势与海拔高度的相关性最好。同一海拔高度上,最高、最低温度在不同年代的增幅具有不一致性:20世纪80年代,二者变化幅度最小;20世纪90年代,二者增幅最大,尤以低海拔地区最为明显。2000 m以上高海拔地区:最高温度和最低温度的变化趋势在20世纪90年代以前变化较小,而在近十年增幅十分明显;日较差季节变化大:夏季减小,冬季增加。20世纪90年代以前,最高、最低温度随海拔高度变化不大,而近20年随海拔高度升高,最高、最低温度的变化趋势几乎都是先减小后增加。高海拔地区比低海拔地区对全球变化反应更明显。     

The Project Siberian High in CMIP5 Models

The Siberian high(SH)experienced a decline from the 1970s to 1990s and a recovery in recent years.The evolution of the SH under global warming is unclear.In this study,41 Coupled Model Intercomparison Project Phase 5(CMIP5)climate models are evaluated in terms of their ability to simulate the temporal evolution of the SH in the 19th and 20th centuries and the spatial pattern of the SH during 1981–2005.The results show that 12models can capture the temporal evolution of the SH center intensity(SHCI)for 1872–2005.The linear correlation coefficient between the SHCI from the Twentieth Century Reanalysis and the simulated SHCI from the multi-model ensemble(MME)of the 12 models is 0.3 on annual and inter-annual scales(above the 99%confidence level).On decadal and multi-decadal time scales,the MME also captures the pronounced reduction(between 1981–2000and 1881–1900 period)and the recovery(during1991–2005)of the SH intensity.Finally,the future evolution of the SH is investigated using the MME of the 12models under the+4.5 and+8.5 W m-2 Representative Concentration Pathway(RCP)scenarios(RCP4.5 and RCP8.5).It is shown that the SHCI,similar to the SHCI in the 20th century,has no significant long-term trend in the 21st century under global warming(RCP8.5 scenario).At the end of 21st century(2081–2100),the SH shows stronger interannual variability than the SH at the end of20th century(1981–2000).The increased interannual variability likely favors the increased interannual variability in winter air temperature over midlatitude Eurasia at the end of 21st century.     

Personal experience with climate change predicts intentions to act

The public's willingness to engage in mitigation actions has not received as much attention as the level of belief in Global Warming (GW), especially on the international stage. Research in Western nations indicates that people systematically misunderstand GW and the actions required for mitigation. Important factors that influence judgments about mitigation actions include personal experiences, beliefs, knowledge, values, and worldviews. We present results of an international survey (25 samples from 24 countries) measuring general intentions to act and willingness to engage in specific actions. Our analysis reveals that endorsement of specific actions is (a) lower than general endorsement of mitigation, (b) accompanied by higher intra-individual variance, and (c) more strongly related to personal experiences with GW. This pattern can be attributed to the compatibility between the proximal construal of specific actions and the nature of the personal experience. Lastly we provide recommendations on how these findings can be used to encourage mitigation action.     

用于测量圆顶视宁度的微温脉动仪的研制

为评价云南天文台丽江2.4m望远镜的圆顶视宁度,研制了一种能测量温度、气压和微温脉动的仪器。在天文圆顶附近,望远镜前方光路上,放置几组微温传感器,可以测得圆顶附近影响天文观测的湍流强度的分布情况。介绍了这套仪器的基本原理,电路设计,程序设计,实验定标以及一个简单的测试。     

东亚区域能量和水分循环对我国极端气候影响研究的一些初步进展

介绍了2009年项目"全球变暖背景下东亚能量和水分循环变异及其对我国极端气候的影响"的主要研究目标和内容,着重叙述了项目实施以来的主要科研进展,包括西北敦煌和临泽区陆气交换加强观测试验、我国极端气候的变化分析和模拟研究以及气候预测新方法和新系统的研制等方面.最后概要介绍了项目未来几年的主要研究工作计划.     

Mapping daily temperature and precipitation in the Qilian Mountains of northwest China

Daily meteorological data are the critical inputs for distributed hydrological and ecological models. This study modified mountain microclimate simulation model （MTCLIM） with the data from 19 weather stations, and compared and validated two methods （the MTCLIM and the modified MTCLIM） in the Qilian Mountains of Northwest China to estimate daily temperature （i.e., maximum temperature, minimum temperature） and precipitation at six weather stations from i January 2000 to 31December 2009. The algorithm of temperature in modified MTCLIM was improved by constructing the daily linear regression relationship between temperature and elevation, aspect and location information. There are two steps to modify the MTCLIM to predict daily precipitation： firstly, the linear regression relationship was built between annual average precipitation and elevation, location, and vegetation index; secondly, the distance weight for measuring the contribution of each weather station on target point was improved by average wind direction during the rainy season. Several regression analysis and goodness-of-fit indices （i.e., Pearson＇s correlation coefficient, coefficient of determination, mean absolute error, root-mean-square error and modelingefficiency） were used to validate these estimated values. The result showed that the modified MTCLIM had a better performance than the MTCLIM. Therefore, the modified MTCLIM was used to map daily meteorological data in the study area from 2000 to 2009. These results were validated using weather stations with short time data and the predicted accuracy was acceptable. The meteorological data mapped could become inputs for distributed hydrological and ecological models applied in the Qilian Mountains.     

An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

Warmer-Get-Wetter or Wet-Get-Wetter? A Criterion to Classify Oceanic Precipitation

In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature(SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project(GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3(ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission(TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1(Had ISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation.