气候变化,土地利用变化和二氧化碳浓度升高对青藏高原总初级生产力的影响（英文）

青藏高原(TP)的生态系统对气候变化,土地利用和土地覆盖变化(LULCC)以及CO_2浓度升高等极为敏感,但这些因素对于TP总初级生产力(GPP)的影响及机理仍不清晰。本研究利用12个陆地生物圈模式定量评估了气候变化, LULCC和CO_2施肥效应对TP的GPP年际变率和趋势影响。结果表明:气候变化对TP的GPP起主导作用,而LULCC和CO_2浓度升高(施肥效应)对GPP年平均值贡献分别为10%和–14%,年际变率贡献为37%和–20%,趋势贡献为52%和–24%。     

太平洋年代际振荡对中国冬季最低气温年代际变化的贡献

基于1961—2013年中国台站的均一化气温数据、NOAA月平均海温资料和CMIP5气候模式数据,利用气候统计手段,定量分析太平洋年代际振荡（PDO）对中国冬季最低气温年代际变化的贡献。结果表明：PDO的年代际序列与年代际滤波后的最低气温场在全国大部分地区呈显著正相关,即PDO负位相时中国冬季最低气温偏低,反之偏高。2006年后中国冬季最低气温变暖减缓,造成这一现象的主要原因是自然变率起到的降温作用,而自然变率又主要由PDO起主导作用,约占自然变率贡献的40%左右。PDO对温度的贡献呈现出明显的年代际变化,在变暖减缓期对升温有明显的负贡献,且负贡献逐渐增大至超过50%。     

局地蒸发和外部水汽输送对松花江流域夏季降水的贡献

本文基于Brubaker二元模型,采用JRA-55再分析资料定量研究了局地蒸发和外部水汽输送对松花江流域夏季气候态降水及其年际变率的相对贡献,并探讨了相应的物理机制。气候平均而言,外部水汽输送是松花江流域初夏（5～6月）和盛夏（7～8月）降水的最主要水汽源。受西风带影响,初夏自西边界进入松花江流域的水汽贡献占主导,外部水汽输送对当地降水的贡献为78.9%,源自蒸发的水汽贡献为21.1%。较之初夏,由于盛夏来自南边界的水汽输送加倍,外部水汽输送贡献增加,外部水汽输送和蒸发对降水贡献分别为86%和14%。JRA-55再分析资料可以合理再现观测降水演变,1961～2016年JRA-55再分析资料降水与观测在初夏与盛夏的相关系数分别可以达到0.73和0.83。研究发现,初夏,由于西南季风异常导致的南边界进入的水汽输送异常是松花江流域降水年际变率的主要原因,自西边界、北边界进入的水汽输送与降水呈现显著负相关,初夏局地蒸发的贡献不显著,该水汽输送异常对应的环流型易发生在El Ni?o衰减年初夏。盛夏来自南边界的水汽输送起主导作用,局地蒸发贡献与降水变化显著负相关,海温强迫作用对该环流异常的强迫并不显著,中高纬度大气内部变率影响占主导。由于盛夏降水与地表温度在盛夏期间显著负相关,盛夏时期降水偏少时,温度偏高,蒸发偏强,进而蒸发水汽对降水贡献增加。     

中国6个CMIP5模式对全球降水年际-年代际变率模拟的定量评估

本文利用美国全球降水气候中心(GPCC)的降水资料和中国参加国际第五阶段耦合模式比较计划(CMIP5)的6个气候模式[BCC_CSM1.1、BCC_CSM1.1(m)、BNU-ESM、FGOALS-s2、FGOALS-g2和FIO-ESM]的历史模拟试验的降水数据,采用可以表征降水变率相对和绝对量级的方法,定量评估了6个模式对降水年际-年代际变率的模拟能力。研究表明,观测降水的年际变率一般占总方差的65%~80%,年代际变率占总方差的10%~35%。在CMIP5历史试验中,6个模式平均的降水年际分量方差对总方差的贡献(超过70%)较观测偏强,模拟降水年代际分量的方差对总方差的贡献较小(约为10%~20%)。模式总体低估了全球平均总降水、年际降水和年代际降水的变率,但是高估了年际降水对总降水的贡献、低估了年代际降水对总降水的贡献。与观测相比,6个模式对东亚和澳大利亚地区的年代际降水的模拟都比较好,模拟与观测年代际降水方差的比值为1左右。在非洲、南美洲和海洋性大陆,BCC_CSM1.1模式模拟的降水年代际变率最接近观测;在欧亚和北美,BNU-ESM模式模拟的降水年代际变率与观测最接近。在欧亚大陆上,BCC_CSM1.1模式模拟的降水年际分量与年代际分量的方差比最接近观测;在非洲和美洲,FGOALS-s2模式模拟的降水年际分量与年代际分量的方差比最接近观测。本文的研究结果有助于理解中国当前气候模式对降水年际-年代际变率的模拟能力,以及未来改进模式。     

1976/1977年前后热带印度洋海表温度年际异常的变化

基于1948～2005年NCEP/NCAR（美国大气研究中心/环境预测中心）再分析资料,讨论了1976/1977年前后的年代际气候变化对热带印度洋海表温度（SST）年际变率特征的影响,结果表明:在气候变化前后,ENSO都能导致热带印度洋SSTA（海表面温度异常）出现全海盆同号的变化,这种模态在冬季最强;气候变化前与变化后相比,该模态对该地区海温年际变率的方差贡献大22.1%, 达到最强的时间早2个月。气候变化前,秋季热带印度洋SSTA的主导年际变率模态表现为全海盆同号,变化后则表现为“偶极子模态”（IODM）。导致上述SSTA特征变化的重要原因,是气候变化前后印度洋风场对ENSO的响应不同。在气候变化前,与ENSO相关联的热带印度洋东风异常首先在夏季出现,而变化后则首先在春季出现,并且有一反气旋性环流异常维持在热带东南印度洋。     

年际气候变率的数值模拟

本文利用IAP GCM 20年的模式输出结果，计算了海平面气压、表面气温和降水的年际气候变率，并与观测资料作了对比分析，以考察模式模拟年际变率的能力。结果表明，模式成功地再现了观测变率地理分布的基本特征，这说明大气内部动力-物理相互作用过程对年际变率有重要影响，而模拟值的偏低则显示了模式中未包括的某些外界强迫因子如海温和海冰年际变化的潜在作用。     

气候模式的年际变率和可预测性

该文研究了大气物理研究所９层格点大气环流模式模拟的年际气候变率，一种试验采用多年平均的观测海温作为下边界条件，另一种试验是有年际变化的实测海温作为下边界条件，两种试验的年际变率分别为记为Ｖ１和Ｖ２，其比值Ｒ（Ｖ２／Ｖ１）则可代表以实测海温为边界条件的模式可预测性，研究结果显示：两种试验的年际变率差异主要热带区，Ｖ２一般大于Ｖ１，并且更接近实际变率，气温和高度场的可预测性在热带区较高，在热带以外区域     

参加CMIP5的四个中国气候模式模拟的东亚冬季风年际变率

本文比较了中国参加“国际耦合模式比较计划”（CMIP5）的四个大气环流模式（即FGOALS-g2、FGOALS-s2、BCC-CSM1-1、BNU-ESM大气模式）在观测海温驱动下,对东亚冬季风（EAWM）气候态和年际变率的模拟能力。结果表明,在气候态上,四个模式均合理再现了EAWM高低层环流系统（包括低层西伯利亚高压（SH）、阿留申低压、异常偏北风、和中高层东亚大槽、西风急流）,其中对2 m气温和500 hPa高度场的模拟技巧最高,四个模式模拟的结果与再分析资料的空间相关系数都达到0.99。在年际变率上,分别对东亚北部地区（30°N～60°N,100°E～140°E）和东亚南部地区（0°～30°N,100°E～140°E）的2 m气温进行经验正交函数分解（EOF）,提取变率主导模态。结果表明,在东亚北部地区,四个模式对2 m气温第一模态（简称“北部型”）的空间分布均有很高的模拟技巧,但只有BNU-ESM能够较好再现其对应的年际变率,其模拟的时间序列与观测的相关系数为0.69。四个模式均能模拟出观测中的3.1 a主导周期,但只有FGOALS-s2和BNU-ESM能模拟出观测中的2.5 a主导周期。在东亚南部地区,模式模拟的前两个主模态共同解释观测中第一模态（简称“南部型”）的特征,其中FGOALS-g2、FGOALS-s2和BNU-ESM的综合模拟技巧较高,但只有BNU-ESM成功再现了观测中2.5 a和3.1 a的主导周期。机理分析表明,FGOALS-g2、FGOALS-s2、BNU-ESM三个模式能合理再现菲律宾海反气旋,同时对南部型有较高的模拟能力,而BCC-CSM1-1则未能有效再现菲律宾海反气旋,使得 BCC-CSM1-1对南部型模拟技巧较低。观测和四个模式模拟的结果一致表现出北极涛动（AO）与北部型PC1呈显著相关,影响大于SH。     

中国半干旱区草甸草原和典型草原碳通量日变化特征

半干旱草原碳收支对陆地生态系统碳源汇功能变化具有重要影响。本文基于通榆草甸草原站2011～2017年和毛登典型草原站2013~2017年涡动相关法观测数据,分析了生长季碳通量日变化特征,研究了碳通量日变化过程对主要环境因子的响应。结果表明:两处草原7月碳吸收活动最强,草甸草原生长季各月总初级生产力（gross primary production, GPP）、生态系统呼吸（ecosystem respiration, R_e）和净碳交换量（net ecosystem exchange, NEE）的峰值均高于典型草原。NEE的日变化以单峰型为主,但7月、8月饱和水汽压差较高时,GPP在正午前后降低,引起NEE的双峰型日变化。光合有效辐射是草甸草原NEE日变化的主导因子,而在典型草原,浅层土壤含水量（5 cm）也主导了NEE日变化。水分亏缺使草原碳交换速率显著降低,草甸草原固碳速率对水分亏缺的敏感性强于典型草原。同时,水分亏缺也改变了GPP、R_e和NEE对温度和光合有效辐射的响应关系。     

春季青藏高原积雪年际变率的年代际转型对东亚夏季风影响的研究进展

冬春青藏高原积雪异常是东亚夏季风的重要预测因子之一。本文系统回顾了近20年关于青藏高原积雪年际变率的年代际转型影响东亚夏季风的相关研究,主要结论如下：（1）20世纪90年代初春季青藏高原积雪的年际变率从东西偶极型转变为全区一致型,这主要受北太平洋、热带大西洋海温异常变化的影响,也与南极涛动、北极涛动的变化密切相关;（2）春季青藏高原积雪年际变率的年代际转型可通过影响东亚高层的副热带西风急流和低层的水汽输送,进而影响东亚夏季风降水格局变化;（3）青藏高原积雪异常可通过“高原大气河”的机制影响梅雨雨带;（4）大西洋年代际振荡可调节春季青藏高原积雪与梅雨降水关系的年代际变化,当大西洋年代际振荡为正（负）位相时,春季青藏高原积雪与梅雨的关系加强（减弱）。最后,本文对青藏高原积雪异常影响东亚季风变化的关键科学问题进行了讨论与展望。     

Climate and Vegetation Drivers of Terrestrial Carbon Fluxes:A Global Data Synthesis

The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.     

Interannual Climate Variability of the Past Millennium from Simulations

The interannual variability of global temperature and precipitation during the last millennium is analyzed using the results of ten coupled climate models participating in the Paleoclimate Modelling Intercomparison Project Phase 3. It is found that large temperature(precipitation) variability is most dominant at high latitudes(tropical monsoon regions), and the seasonal magnitudes are greater than the annual mean. Significant multi-decadal-scale changes exist throughout the whole period for the zonal mean of both temperature and precipitation variability, while their long-term trends are indistinctive. The volcanic forcings correlate well with the temperature variability at midlatitudes, indicating possible leading drivers for the interannual time scale climate change.     

Interannual variability and expected regional climate change over North America

This study aims to analyse the interannual variability simulated by several regional climate models (RCMs), and its potential for disguising the effect of seasonal temperature increases due to greenhouse gases. In order to accomplish this, we used an ensemble of regional climate change projections over North America belonging to the North American Regional Climate Change Program, with an additional pair of 140-year continuous runs from the Canadian RCM. We find that RCM-simulated interannual variability shows important departures from observed one in some cases, and also from the driving models’ variability, while the expected climate change signal coincides with estimations presented in previous studies. The continuous runs from the Canadian RCM were used to illustrate the effect of interannual variability in trend estimation for horizons of a decade or more. As expected, it can contribute to the existence of transitory cooling trends over a few decades, embedded within the expected long-term warming trends. A new index related to signal-to-noise ratio was developed to evaluate the expected number of years it takes for the warming trend to emerge from interannual variability. Our results suggest that detection of the climate change signal is expected to occur earlier in summer than in winter almost everywhere, despite the fact that winter temperature generally has a much stronger climate change signal. In particular, we find that the province of Quebec and northwestern Mexico may possibly feel climate change in winter earlier than elsewhere in North America. Finally, we show that the spatial and temporal scales of interest are fundamental for our capacity of discriminating climate change from interannual variability.     

Adaptive management to climate change for Norway spruce forests along a regional gradient in Finland

We hypothesized that the responses of boreal Norway spruce (Picea abies) forests to climate change would be region-specific due to regional differences in temperature and water availability. In this context, we analyzed the adaptive effects of varied thinning intensities on the gross primary production (GPP), total stem wood growth, and timber yield over a 100-year period using a process-based ecosystem model. Our simulations represented Norway spruce forests for five different bioclimatic zones spanning southern to northern Finland (61–67^oN). Ten thinning regimes with thinning intensities ranging from 5 to 50 %, as well as an unthinned regime, were included in the calculations. The results showed that at the southern sites without thinning, the cumulative GPP and total stem wood growth were lower under the changing climate than in the current climate over the simulation period due to greater water depletion via evapotranspiration and reduced soil water availability. At the central and the northern sites, the climate changes increasingly enhanced the GPP and total stem wood growth due to the mitigation of low-temperature limitation and the improved soil water availability. Thinning generally mitigated the soil water deficit by reducing water evaporation and led to a reduction of the natural mortality. At the southern sites, light and moderate thinning intensities increased the GPP and total stem wood growth relative to sites with a changing climate that experienced no thinning. Moreover, moderate thinning resulted in the greatest timber yield. Heavy thinning, in which a large proportion of standing trees were removed, reduced the GPP and total stem wood growth despite allowing increased soil water availability. At the northern sites, all levels of thinning, including light thinning, decreased the GPP and stem wood growth, indicating that soil water availability was not a limiting factor for growth prior to thinning.     

Potential impacts of land-use on climate variability and extremes

This study aims at exploring potential impacts of land-use vegetation change (LUC) on regional climate variability and extremes. Results from a pair of Australian Bureau of Meteorology Research Centre (BMRC) climate model 54-yr (1949-2002) integrations have been analysed. In the model experiments, two vegetation datasets are used, with one representing current vegetation coverage in China and the other approximating its potential coverage without human intervention. The model results show potential impacts ...     

Atmospheric radiative feedbacks associated with transient climate change and climate variability

This study examines in detail the ‘atmospheric’ radiative feedbacks operating in a coupled General Circulation Model (GCM). These feedbacks (defined as the change in top of atmosphere radiation per degree of global surface temperature change) are due to responses in water vapour, lapse rate, clouds and surface albedo. Two types of radiative feedback in particular are considered: those arising from century scale ‘transient’ warming (from a 1% per annum compounded CO₂ increase), and those operating under the model’s own unforced ‘natural’ variability. The time evolution of the transient (or ‘secular’) feedbacks is first examined. It is found that both the global strength and the latitudinal distributions of these feedbacks are established within the first two or three decades of warming, and thereafter change relatively little out to 100 years. They also closely approximate those found under equilibrium warming from a ‘mixed layer’ ocean version of the same model forced by a doubling of CO₂. These secular feedbacks are then compared with those operating under unforced (interannual) variability. For water vapour, the interannual feedback is only around two-thirds the strength of the secular feedback. The pattern reveals widespread regions of negative feedback in the interannual case, in turn resulting from patterns of circulation change and regions of decreasing as well as increasing surface temperature. Considering the vertical structure of the two, it is found that although positive net mid to upper tropospheric contributions dominate both, they are weaker (and occur lower) under interannual variability than under secular change and are more narrowly confined to the tropics. Lapse rate feedback from variability shows weak negative feedback over low latitudes combined with strong positive feedback in mid-to-high latitudes resulting in no net global feedback—in contrast to the dominant negative low to mid-latitude response seen under secular climate change. Surface albedo feedback is, however, slightly stronger under interannual variability—partly due to regions of extremely weak, or even negative, feedback over Antarctic sea ice in the transient experiment. Both long and shortwave global cloud feedbacks are essentially zero on interannual timescales, with the shortwave term also being very weak under climate change, although cloud fraction and optical property components show correlation with global temperature both under interannual variability and transient climate change. The results of this modelling study, although for a single model only, suggest that the analogues provided by interannual variability may provide some useful pointers to some aspects of climate change feedback strength, particularly for water vapour and surface albedo, but that structural differences will need to be heeded in such an analysis.     

Climate change at the ecosystem scale: a 50-year record in New Hampshire

Observing the full range of climate change impacts at the local scale is difficult. Predicted rates of change are often small relative to interannual variability, and few locations have sufficiently comprehensive long-term records of environmental variables to enable researchers to observe the fine-scale patterns that may be important to understanding the influence of climate change on biological systems at the taxon, community, and ecosystem levels. We examined a 50-year meteorological and hydrological record from the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, an intensively monitored Long-Term Ecological Research site. Of the examined climate metrics, trends in temperature were the most significant (ranging from 0.7 to 1.3 °C increase over 40–50 year records at 4 temperature stations), while analysis of precipitation and hydrologic data yielded mixed results. Regional records show generally similar trends over the same time period, though longer-term (70–102 year) trends are less dramatic. Taken together, the results from HBEF and the regional records indicate that the climate has warmed detectably over 50 years, with important consequences for hydrological processes. Understanding effects on ecosystems will require a diversity of metrics and concurrent ecological observations at a range of sites, as well as a recognition that ecosystems have existed in a directionally changing climate for decades, and are not necessarily in equilibrium with the current climate.     

Ocean–atmosphere Teleconnections Play a Key Role in the Interannual Variability of Seasonal Gross Primary Production in China

Since the 1950s, the terrestrial carbon uptake has been characterized by interannual variations, which are mainly determined by interannual variations in gross primary production (GPP). Using an ensemble of seven-member TRENDY (Trends in Net Land–Atmosphere Carbon Exchanges) simulations during 1951–2010, the relationships of the interannual variability of seasonal GPP in China with the sea surface temperature (SST) and atmospheric circulations were investigated. The GPP signals that mostly relate to the climate forcing in terms of Residual Principal Component analysis (hereafter, R-PC) were identified by separating out the significant impact from the linear trend and the GPP memory. Results showed that the seasonal GPP over China associated with the first R-PC1 (the second R-PC2) during spring to autumn show a monopole (dipole or tripole) spatial structure, with a clear seasonal evolution for their maximum centers from springtime to summertime. The dominant two GPP R-PC are significantly related to Sea Surface Temperature (SST) variability in the eastern tropical Pacific Ocean and the North Pacific Ocean during spring to autumn, implying influences from the El Ni?o–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). The identified SST and circulation factors explain 13%, 23% and 19% of the total variance for seasonal GPP in spring, summer and autumn, respectively. A clearer understanding of the relationships of China’s GPP with ocean–atmosphere teleconnections over the Pacific and Atlantic Ocean should provide scientific support for achieving carbon neutrality targets.     

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941     

Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments

This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.