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.     

中国贝类养殖对海洋碳循环的贡献评估

造成全球暖化的主要原因是温室气体的过量排放,其中CO2的贡献率达60 %,贝类养殖具有碳沉积作用。依据农业部渔业局编制的《中国渔业统计年签》,以2001年到2010年的年平均产量计算贝类捕获和养殖的碳沉积能力,并评估其碳沉积潜力;计算牡蛎、蛤、扇贝与贻贝四种贝壳单位面积的碳沉积能力并与森林、珊瑚礁的碳沉积能力进行比较分析。本文对我国浅海贝类养殖所具有的碳沉积能力进行评估,以了解贝类养殖对海洋碳循环的贡献,可为争取国家碳份额的合法权益提供基础数据。分析表明我国近十年贝类总产量稳定在1100万吨以上,并有增加的趋势,其中海水养殖贝类约占87.34 %。贝类养殖和捕获总产量的碳沉积和海水养殖产量的碳沉积量分别为58.57、51.15万吨/年,碳沉积能力分别相当于122.28、106.78万公顷的造林,可分别减少大气CO2增加量的0.0125 %、0.0109 %。牡蛎、蛤、扇贝与贻贝的单位面积碳沉积速率分别为1.573、0.388、0.301、1.039吨碳/(公顷?年);牡蛎和贻贝高于森林的碳沉积能力0.479吨碳/(公顷?年);但低于珊瑚礁的碳沉积能力1.8吨碳/(公顷?年)。我国贝类淡、海水养殖产量可分别创造约268.4万元/年、12,711.2万元/年的碳权商机。     

Chinese Contribution to CMIP5：An Overview of Five Chinese Models’Performances

An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 （CMIP5） is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 pro ject are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interan-nual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change pro jection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface tem-perature （SST） mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation （MJO） amplitude and tropical cyclone Genesis Potential Index （GPI）, global monsoon precipitation pattern, El Ni-no-Southern Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO） related SST anomalies. However, the perfor-mances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific mon-soon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways pro jection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.     

论气候变暖背景下干旱和干旱灾害风险特征与管理策略简

The drought is a most severe natural disaster worldwide, which leads to great risk in human being. The drought disaster and risk have more prominent because of obvious climatic warming in the last hundred years. At present, the understanding of the internal laws of the occurrence of drought and drought risk is not comprehensive, and the recognition of the characteristics of the drought and drought risk under climatic warming is obscure. In this paper, we summarized systematically the domestic and overseas research progress of the drought and drought disaster risk, introduced the principle of the drought disaster transfer process and the essential features of drought disaster, analyzed synthetically the main characteristics and interactions among the key factors of the drought disaster risk, discussed the effect of climatic warming on drought and drought disaster risk, and probed into the basic requirement of drought disaster risk management. Above all, we provide the main protective measurements of the drought disaster and the main strategy of drought disaster risk management.     

Studies on the Coral Reefs of the South China Sea: From Global Change to Oil-Gas Exploration

Studies on the coral reefs of the South China Sea (SCS) was the theme of the 6th Session of the 3rd Conference on Earth System Science (CESS) in Shanghai, 2014. This session discussed the most recent study developments on the SCS coral reefs, including coral reefs’ responses to global changes, coral reefs’ records on past climatic variations, and the activities about constructions and oil gas explorations in the coral reefs areas of the SCS. Disturbed by intensive anthropogenic activities and global climate warming, coral reefs in the SCS have declined dramatically, reflecting the up to 80% decrease of living coral cover and many areas having less than 20% of living coral cover. Geochemical data of SCS coral skeletons clearly show that since the Industry Revolution, the pollution situation of the SCS have dramatically increased and the seawater pH values have been continuously lowering, i.e. oceanic acidification. All these environmental phenomenon are further stressing the healthy development of the coral reef ecosystem in the SCS. Meanwhile, the poor coral reef ecosystems in the SCS are facing more anthropogenic disturbances such as coastal developments and engineering constructions. Obviously, the SCS coral reefs will be faced with more environmental challenges in the coming future. We therefore suggest that the policy makers should realize the extreme importance and the fragile of the coral reef ecosystems, and scientifically and with great cautions design construction project when in coral reef areas. We initiated the concept of “green engineering” for future developments in coral reef areas. Coral reefs are widely spreading in the whole SCS, and most of them developed since Miocene. Variations in coral reef structures provide good future oil-gas exploration. Because the SCS coral reefs have a long-developing history and a wide spatial distribution, they provide great potential in recording past environmental changes.     

全新世温度研究回顾及对历史人地关系的启示

最新一些研究结果强调了全新世期间的长期增温趋势,综合全球平均海平面、大陆冰盖面积、大气温室气体和太阳辐射证据来看,这比传统观点所认为的全新世期间的长期降温趋势,更具有合理性。回顾历史,结合最新的一些研究进展,发现支持“中全新世大暖期”和“晚全新世降温趋势”的证据存在明显的不确定性,最核心的问题为晚全新世加强的人类活动对代用指标或者证据的强烈扰动,使得其不能准确地反映真实的气候变化过程。鉴于目前全新世温度历史争论的核心关键在于晚全新世,因此有必要加强晚全新世温度变化研究。在人类活动影响较小的地区,或者利用对人类活动不敏感的代用指标开展研究,有望可以获得更可靠的晚全新世温度历史重建结果,为准确认识中华数千年文明的长期温度变化背景,进而理解期间的“人地关系”演化历史,并最终客观认识现今面临的以全球变暖为主要特征的气候环境问题,提供一定的科学基础。     

短期增温和降水减少对沙质草地土壤微生物量碳氮和酶活性的影响

通过模拟气候变化,探究短期增温和降水减少对沙质草地土壤微生物量碳氮及酶活性的影响,揭示沙质草地土壤微生物量碳氮和酶活性对短期气候变化的响应规律。结果表明：（1）短期增温和降水减少对土壤微生物量碳氮和酶活性均产生显著影响。（2）在自然温度下,与自然降水相比,降水减少40%时土壤微生物量碳（MBC）和微生物氮（MBN）含量最高,增幅分别为87.9%和98.8%;降水减少60%时土壤碱性蛋白酶（S-ALPT）活性最低,降幅达32.8%。（3）在增温条件下,与自然降水相比,降水减少40%时土壤MBC和MBN含量最低,降幅分别为25.67%和48.16%,土壤脲酶（S-UE）活性最高,增幅20.42%。（4）土壤pH与3种土壤酶活性正相关,与土壤微生物量碳氮负相关。土壤微生物量碳氮与土壤纤维素酶（S-CL）活性负相关,与S-UE、S-ALPT活性正相关。