Study of temperature and precipitation variations in Italy based on surface instrumental observations

In this paper we present a study concerning the climatic behaviour of two principal observables, temperature and precipitation as obtained from the measurements carried out at 50 Italian meteorological stations, since 1961. Analyses of WMO Climate Normals (CliNo) from 1961 to 1990 have been performed dividing the 50 Italian stations in three different classes: mountain (11 stations), continental (17) and coastal areas (21).The comparison of the CliNo 1961–1990 with the trend of temperature and precipitation for the period 1991–2000 showed a sharp significant increase of summer temperatures over Italy starting from 1980. This phenomenon was particularly evident for mountain stations, where a significant temperature increase has been recorded also during the autumn. Moreover, the analysis of precipitation data permitted to point out that, starting from 1980, mountain stations have been affected by a significant increase of precipitation events during autumn and winter, while for the rest of the Italian territory a reduction of precipitations has been recorded during early spring.     

全球变暖减缓背景下欧亚秋冬温度变化特征和原因

采用气候序列变化趋势诊断和一元线性回归等分析法,研究和讨论了2000-2012年和1976-1999年两种年代际背景下全球陆地不同区域的年平均地表温度的变化特征。发现欧亚大陆中高纬度地区是对全球变暖减缓贡献最大的区域。且该地区在2000年以来秋季年代际增温,而冬季年代际降温。从同期大气环流的配置来看,在对流层低层,秋季西伯利亚高气压年代际减弱,而冬季西伯利亚高气压年代际增强。在对流层中高层,秋季从西欧至东北亚为"高-低-高"的高度场异常分布,纬向环流加强,经向环流减弱,而冬季极地与贝加尔湖地区的高度场呈偶极型分布,东亚大槽加深,经向环流加强。进一步研究发现,超前一个季节的喀拉海附近的海冰与欧亚中高纬度秋冬两季温度的年代际变率有着密切的联系。一方面,夏季(秋季)海冰减少影响秋季(冬季)中高纬度大气环流;另一方面,夏季(秋季)海冰减少,使得秋季(冬季)从北极至中高纬度大陆的对流层低层水汽含量增加(减少),大气逆辐射增强(减弱)导致秋季(冬季)增温(降温)。     

东北地区水稻障碍型低温冷害变化对区域气候增暖的响应

利用东北地区153个气象站1961—2010年逐日气温资料,采用统计学方法分析了水稻障碍型低温冷害的气候变化特征及其对区域气候变暖的响应情况。结果表明,东北大部地区水稻障碍型低温冷害事件呈减少趋势,但区域性较为明显;障碍型低温冷害对关键发育期气温变化响应较为敏感,二者呈显著的负相关关系,表现为气温每升高1 ℃,东北地区冷害减少35个站次。东北地区关键发育期气温均呈上升趋势,但吉林西部地区障碍型冷害却随之增加,分析了关键发育期气温变率和气候变率,将其解释为局地障碍型冷害增加主要受气候变率增大的影响,逐日气温变率对其影响不大。     

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.     

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.     

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.     

Assessment of Historical Climate Trends of Surface Air Temperature in CMIP5 Models

This study assesses the historical climate trends of surface air temperature（SAT）, their spatial distributions, and the hindcast skills for SAT during 1901– 2000 from 24 Coupled Model Intercomparison Project Phase 5（CMIP5） models. For the global averaged SAT, most of the models（17/24） effectively captured the increasing trends（0.64°C/century for the ensemble mean） as the observed values（- 0.6°C/century） during the period of 1901–2000, particularly during a rapid warming period of 1970–2000 with the small model spread. In addition, most of the models（22/24） showed high hindcast skills（the correlation coefficient, R 〉 0.8）. For the spatial pattern of SAT, the models better simulated the relatively larger warming at the middle-to-high latitudes in the Northern Hemisphere than that in the Southern Hemisphere and the greater warming on the land than that in the ocean between 40°S and 40°N. The simulations underestimated the warming along some ocean boundaries but overestimated warming in the Arctic Ocean. Most of the coupled models were able to reproduce the large-scale features of SAT trends in most regions excluding Antarctica, some parts of the Pacific Ocean, the North Atlantic Ocean near Greenland, the southwestern Indian Ocean, and the Arctic Ocean. The outgoing longwave radiation（OLR） and incoming shortwave radiation（ISR） at the top of the atmosphere（TOA） and the downward longwave（LW） radiation and sensible heat flux at the surface had positive contributions to the increasing trends in most of the models.     

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

The northern Indian Ocean （NIO） experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emis- sion changes, and there are still large uncertainties in the representation of the aerosol indirect effect （ALE） in CMIP5 （Coupled Model Intercomparison Project Phase 5） models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux （FSDS） at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases （GHGs）. The FSDS decreasing trend is mostly contrib- uted by the decreasing trend of cloudy-sky surface downwelling shortwave flux （FSDSCL）, a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux （FSDSC）. Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicat- ing that the strength of the AIE in these models may be overestimated in the NIO.