Impact of the Ice-albedo Feedback on Meridional Temperature Gradient of Northern Hemisphere

This paper analyzes the variation of meridional temperature gradient (MTG) over mid-latitude and high-latitude of Northern Hemisphere continents during last 100 years using observational data. It is found that MTG over high-latitude of Northern Hemisphere continents has an increasing trend, but the simulation results of CMIP5 models show a decreasing trend. Results of this study showed the decrease of MTG over the high-latitude continents of Northern Hemisphere calculated by CMIP5 historical simulations mainly because the models of CMIP5 exaggerated ice-albedo feedback over high-latitude regions. A series of simulation results by energy balance climate models showed that ice-albedo feedback amplified the magnitude of warming in the global warming induced only by carbon dioxide, and the magnitude of warming in high latitude was much larger than that in low-latitude regions. Along with global warming, ice-albedo feedback has little influence on MTG in low-latitude, but can induce the decrease of MTG in high-latitude regions.     

Surface air temperature changes over the Tibetan Plateau: Historical evaluation and future projection based on CMIP6 models

With its amplification simultaneously emerging in cryospheric regions, especially in the Tibetan Plateau, global warming is undoubtedly occurring. In this study, we utilized 28 global climate models to assess model performance regarding surface air temperature over the Tibetan Plateau from 1961 to 2014, reported spatiotemporal variability in surface air temperature in the future under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), and further quantified the timing of warming levels (1.5, 2, and 3 °C) in the region. The results show that the multimodel ensemble means depicted the spatiotemporal patterns of surface air temperature for the past decades well, although with differences across individual models. The projected surface air temperature, by 2099, would warm by 1.9, 3.2, 5.2, and 6.3 °C relative to the reference period (1981–2010), with increasing rates of 0.11, 0.31, 0.53, and 0.70 °C/decade under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios for the period 2015–2099, respectively. Compared with the preindustrial periods (1850–1900), the mean annual surface air temperature over the Tibetan Plateau has hit the 1.5 °C threshold and will break 2 °C in the next decade, but there is still a chance to limit the temperature below 3 °C in this century. Our study provides a new understanding of climate warming in high mountain areas and implies the urgent need to achieve carbon neutrality.     

基于CMIP6模式数据的1961—2100年青藏高原地表气温时空变化分析

基于第六次国际耦合模式比较计划（CMIP6）的22个地球气候/系统模式模拟数据,分析了1961—2100年期间青藏高原年均地表气温在不同情景下的时空变化。结果表明,多模式集合平均的模拟结果优于大多数单个模式。由于共享社会经济路径（SSP）和辐射强迫的不同,在SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5四种情景下,2015—2100年间青藏高原年均地表气温的增温趋势分别为0.10 ℃·（10a）^-1、0.29 ℃·（10a）^-1、0.53 ℃·（10a）^-1和0.69 ℃·（10a）^-1,帕米尔高原、藏北高原中西部和巴颜喀拉山区为三个升温中心。相对于1995—2014年参考时段,到本世纪中期（2041—2060年）,青藏高原区域年均地表气温将分别增加1.37 ℃、1.72 ℃、1.98 ℃和2.30 ℃,而到本世纪末期（2081—2100年）,年均地表气温将分别增加1.42 ℃、2.65 ℃、4.28 ℃和5.38 ℃。与《巴黎协定》提出的到本世纪末全球平均气温升高不超过2 ℃目标相比,无论在哪种情景下,到本世纪中期时青藏高原年均地表气温相对于工业革命前均升高超过2 ℃,这会造成极大的气候生态环境问题。     

A 19<Superscript>th</Superscript> Century Baseline Temperature Estimate for Peninsular India from Combined Analysis of Geothermal and Meteorological Records

Direct information about climate change from meteorological surface air temperature records are available in India only since 1901 A.D. Meteorological surface air temperature (SAT) data for the period 1901–2006 from 49 sites in peninsular India have been combined with the geothermal data from 146 sites to extract a baseline (or pre-observational mean, POM) surface temperature prior to the existence of the observational record in the region. Periodicities of 5, 11 and 22 years in the SAT time series have little influence on the combined analysis to infer long-term climate change. The best estimate of the long-term average temperature for the 19^th Century is 0.7 °C lower than the 1961–1990 mean temperature. Considering the additional warming of 0.38°C relative to the 1961–1990 mean over a 10-year window centred on the year 2000, the hybrid POM-SAT method suggests that the total surface warming in peninsular India from mid-1800s to early- 2000s is about 1.1 °C. The study provides new evidence for significant warming prior to the establishment of widespread meteorological stations in peninsular India.     

Projections of temperature changes over South America during the twenty-first century using CMIP6 models

A 22-member ensemble from CMIP6 is used to analyze the projected changes and seasonal behavior in surface air temperature over South America during the twenty-first century. In the future projections, CMIP6 models shown a high dependency to the socioeconomic pathway over each country of South America. The multimodel ensemble projects a continuous increase in the annual mean temperature over South America during the twenty-first century under the three future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5). Besides, it was possible to identify consistent positive trends across all the models, with values between 0.45 ± 0.05 and 2.05 ± 0.31 °C cy⁻¹ under the historical experiment, however largest trends occurs for the projection periods (near, mid and far future), with values between − 0.87 ± 0.84 to 2.88 ± 0.60 °C cy⁻¹ (SSP1-2.6), 1.41 ± 0.88 to 5.32 ± 0.81 °C cy⁻¹ (SSP2-4.5) and 4.75 ± 0.58 to 8.76 ± 0.74 °C cy⁻¹ (SSP5-8.5) with maximum values at Bolivia, Brasil, Paraguay and Venezuela whilst minimum values for Argentina and Uruguay, regardless of the SSP scenario used. From the seasonal behavior analysis was possible to identify maximum values between January and March whilst minimum between June and July, except in Brasil, Venezuela and Guyana–Surinam–French Guayana, with annual range decreasing as the latidude decreases. By the end of the twenty-first century the annual mean temperature over South america is projected to increase between 0.92–2.11 °C, 0.97–3.37 °C and 1.27–6.14 °C under SSP1-2.6, SSP2-4.5 and SSP5-8.5 projection scenarios respectively. This projected increase of temperature across the continent will produce negative repercussions in the social, economic and political spheres. The results obtained in this study provide insights about the CMIP6 performance over this region, which can be used to develop adaptation strategies and might be useful for the adaptation to the climate change.

     

基于CMIP6模式的黄河上游地区未来气温模拟预估

利用第六次国际耦合模式比较计划（CMIP6）提供的5个气候模式,并结合基于地面气象站的CN05.1气象资料,评估了CMIP6模式对黄河上游地区1961—2014年气温变化的模拟能力。基于7个共享社会经济路径及代表性浓度路径（SSP-RCP）组合情景,结合多模式集合平均预估了2015—2100年黄河上游地区年均气温和季平均气温的时空变化规律。结果表明：多模式集合平均能较好地模拟黄河上游地区历史平均气温的空间分布格局与年变化。7个未来情景一致表明,2015—2100年黄河上游地区年平均气温呈现波动上升趋势［0.03～0.82 ℃?（10a）^-1］。其中,低辐射强迫情景下（SSP1-1.9、SSP1-2.6及SSP4-3.4）气温先呈现增加趋势,21世纪中期到达增幅峰值,之后增温呈现放缓趋势;而中、高辐射强迫情景下（SSP2-4.5、SSP3-7.0、SSP4-6.0及SSP5-8.5）气温表现为持续上升态势。空间上,未来气温增幅显著的区域位于黄河上游西部地区;时间上,呈现夏季增温快,春季增温慢。四季增温的空间分布呈现出一致特征,表现为西部增温强于东部,北部增温强于南部。研究结果可为黄河流域水资源管理及气候变化的适应性研究提供科学依据。     

Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China

Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China. Evaluation of long-term aerosol optical depth (AOD) data from models and reanalysis, can greatly promote understanding of spatiotemporal variations in air pollution in China. To do this, AOD (550 nm) values from 2000 to 2014 were obtained from the Coupled Model Inter-comparison Project (CIMP6), the second version of Modern-Era Retrospective analysis for Research, and Applications (MERRA-2), and the Moderate Resolution Imaging Spectroradiometer (MODIS; flying on the Terra satellite) combined Dark Target and Deep Blue (DTB) aerosol product. We used the Terra-MODIS DTB AOD (hereafter MODIS DTB AOD) as a standard to evaluate CMIP6 Ensemble AOD (hereafter CMIP6 AOD) and MERRA-2 reanalysis AOD (hereafter MERRA-2 AOD). Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD, than between CMIP6 and MODIS DTB AOD, in most regions of China, at both annual and seasonal scales. However, significant under- and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD. The long-term (2000–2014) MODIS DTB AOD distributions show the highest AOD over the North China Plain (0.71) followed by Central China (0.69), Yangtse River Delta (0.67), Sichuan Basin (0.64), and Pearl River Delta (0.54) regions. The lowest AOD values were recorded over the Tibetan Plateau (0.13 ± 0.01) followed by Qinghai (0.19 ± 0.03) and the Gobi Desert (0.21 ± 0.03). Large amounts of sand and dust particles emitted from natural sources (the Taklamakan and Gobi Deserts) may result in higher AOD in spring compared to summer, autumn, and winter. Trends were also calculated for 2000–2005, for 2006–2010 (when China introduced strict air pollution control policies during the 11th Five Year Plan or FYP), and for 2011–2014 (during the 12th FYP). An increasing trend in MODIS DTB AOD was observed throughout the country during 2000–2014. The uncontrolled industrialization, urbanization, and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD. Finally, China's air pollution control policies helped to reduce AOD in most regions of the country; this was more evident during the 12th FYP period (2011–2014) than during the 11th FYP period (2006–2010). Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality.     

Comparison of Simulated and Reconstructed Temperature in China during the past 2000 years

Studying climate changes over the past 2 000 years has important scientific significance in exploring climate variability on decadal to centennial timescales, assessing the natural and anthropogenic contribution to the climate warming, and understanding the effects of human activities in the past and future climate changes. Due to the scarcity of observation and uncertainty of reconstruction in this period, climate model is developed as a useful tool for studying paleoclimate.The Community Earth System Model (CESM) is one of the state-of-the-art climate models, but its performance in simulating the temperature in China has not been examined.The temperature datasets of observation/reanalysis (GHCN_CAMS) and reconstructions during the past 2000 years in China were used to examine the performance of CESM. The comparison between the annual average temperatures of GHCN_CAMS reanalysis and simulation showed that the model well reproduced the spatial distributions and upward trend of the annual average temperature in China, and the comparison with reconstructions in five sub-regions of China indicated that the simulation were in good consistent with the average temperature changes of reconstructionson decadal time scales. On the centennial time scale, the average temperature fluctuations of simulation in the regions of China were in accord with reconstructions generally except for Central East and Tibet.There existed three warm periods of simulated temperature variation in China over the past 2000 years, including 0-540AD, 800-1250AD and 1901-2000AD, and two cold periods involving the 551-721AD and 1400-1850AD, which had some discrepancies with reconstructions. And the discrepancies between simulation and reconstructions might be related to uncertainties of the resolution, external forcing and parameterization of the subgrid-scale process in the model.     

Assessment of the seasonal variation of simulated Wyrtki jet over the tropical Indian Ocean in CMIP5 models

Performances of the 24 Coupled Model Intercomparison Project Phase 5 (CMIP5) models in simulating the Wyrtki Jet over the tropical Indian Ocean are evaluated, and the results show large diversity in the simulated current intensity at seasonal timescale. These coupled models are able to capture the dominant spatial distribution of observed Wyrtki Jet, the central equatorial region. The simulated seasonal variations of Wyrtki Jet are also reproduced quantitatively, though the simulated amplitudes from CMIP5 models are quite spread among the CMIP5 models. Compared with the observation, some coupled models are not able to present the evolution of Wyrtki Jet in fall season and the decay phase has been postponed 1 month later. Further diagnostic illustrates that the simulated surface zonal wind has remarkable impact on the evolution of Wyrtki Jet in fall season over the tropical Indian Ocean. This study also points out that there is a common problem in these models that most of them present 1-month delayed Wyrtki Jets peak time than the normal climatological condition along the center equatorial Indian Ocean.     

Recent trends of temperature and precipitation proxies in Saudi Arabia: implications for climate change

The objective of the present study was to reconstruct a short-term (12–14 years) trend of surface temperature and precipitation patterns using their surrogates as provided by satellite images for selected locations along the Red Sea mountains in Saudi Arabia. Time series land surface temperature (LST) and normalized difference vegetation index (NDVI) data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite were temporally plotted to delineate the trend and the decadal rates of change of both parameters. Results showed that real climate change is reported in the study area during the study period. There is a net increasing in the surface temperatures by 0.45 to 1.2 °C/decade and a net decrease in annual rainfall between 2001 and 2014. Findings of the present study show that the region is under a warming of the climate and a declining of wetness, which coincide with the air temperature and rainfall trends obtained from meteorological stations.     

新疆21世纪气候变化的高分辨率模拟

使用一个25 km高水平分辨率区域气候模式(RegCM3),嵌套MIROC3.2_hires全球气候模式结果,进行了IPCC SRES A1B情景下,东亚区域21世纪气候变化的模拟,针对新疆地区进行了分析.首先对模式模拟的当代（1981-2000年）气候进行检验,结果表明:模式对年平均气温、降水的空间分布和数值均具有较...     

Understanding the past to interpret the future: comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.     

CMIP5和CMIP6模式在历史试验下对AMO和PDO的模拟评估

利用Hadley中心的观测海温资料,以及耦合模式比较计划的第五阶段和耦合模式比较计划的第六阶段历史试验的模式资料,分析和评估了2个最为重要的年代际尺度模态,北大西洋年代际振荡、太平洋年代际振荡在耦合模式比较计划的第五阶段和耦合模式比较计划的第六阶段中的模拟能力。通过对比多模式集合发现,在空间模态方面,耦合模式比较计划的第五阶段和耦合模式比较计划的第六阶段都能模拟出北大西洋年代际振荡在北大西洋地区的信号,但耦合模式比较计划的第六阶段的模拟更好,对于太平洋年代际振荡模态而言,都能模拟出在北太平洋地区的信号,而太平洋年代际振荡在热带太平洋地区的信号,耦合模式比较计划的第六阶段模拟的振幅明显更接近观测。在周期的模拟方面,耦合模式比较计划的第五阶段和耦合模式比较计划的第六阶段结果相似,都能模拟出北大西洋年代际振荡存在60~70年的周期,以及太平洋年代际振荡存在20年和60~70年的双周期。整体而言,耦合模式比较计划的第六阶段相比于耦合模式比较计划的第五阶段在空间特征模拟方面有一定进步,但是对于周期的模拟能力,没有明显进步。     

A review of observed and projected changes in climate for the islands in the Caribbean

Observed and projected changes in climate have serious socio-economic implications for the Caribbean islands. This article attempts to present basic climate change information—based on previous studies, available observations and climate model simulations—at spatial scales relevant for islands in the Caribbean. We use the General Circulation Model (GCM) data included in the Coupled Model Intercomparison Project phase 3 (CMIP3) and the UK Hadley Centre regional climate model (RCM) data to provide both present-day and scenario-based future information on precipitation and temperature for individual island states. Gridded station observations and satellite data are used to study 20th century climate and to assess the performance of climate models. With main focus on precipitation, we also discuss factors such as sea surface temperature, sea level pressure and winds that affect seasonal variations in precipitation. The CMIP3 ensemble mean and the RCM successfully capture the large-scale atmospheric circulation features in the region, but show difficulty in capturing the characteristic bimodal seasonal cycle of precipitation. Future drying during the wet season in this region under climate change scenarios has been noted in previous studies, but the magnitude of change is highly uncertain in both GCM and RCM simulations. The projected decrease is more prominent in the early wet season erasing the mid-summer drought feature in the western Caribbean. The RCM simulations show improvements over the GCM mainly due to better representation of landmass, but its performance is critically dependent on the driving GCM. This study highlights the need for high-resolution observations and ensemble of climate model simulations to fully understand climate change and its impacts on small islands in the Caribbean.     

基于CMIP6气候模式的新疆积雪深度时空格局研究

积雪深度的变化对地表水热平衡起着至关重要的作用。选用了国际耦合模式比较计划第六阶段（CMIP6）中目前情景比较齐全的五个全球气候模式,通过对比新疆地区1979—2014年积雪深度长时间序列数据集,评估了气候模式在新疆地区模拟积雪深度的模拟能力,接着预估了未来不同SSPs-RCPs情景下新疆地区在2021—2040年（近期）、2041—2060年（中期）、2081—2100年（末期）相对于基准期（1995—2014年）的积雪深度变化。气温和降水对积雪深度变化有着重要的影响,因此还分析了新疆地区到21世纪末期气温和降水的变化趋势。结果表明：订正后的气候模式模拟的积雪深度数据与观测数据的相关系数均达到0.8以上,其中1月至3月与观测数据的结果更为吻合。气候模式基本上能够反映积雪深度年内变化的基本特征,气候模式模拟的积雪深度空间分布和观测数据具有相似的特征。气温和降水在未来不同情景下均会波动上升,其中气温的增幅相对比较明显,达0.43 ℃·（10a）^-1,而降水的增幅为0.63 mm·（10a）^-1,新疆未来的气候总体上呈现出变暖变湿的趋势。新疆地区的平均积雪深度在未来不同时期相对基准期均呈增加的趋势。SSP1-1.9情景下,21世纪近期、中期和末期北部大部分地区的积雪深度将会有所增加;SSP1-2.6情景下,北部阿尔泰山地区的积雪深度在21世纪近期有所减小,但中期和末期将会有所增加;SSP2-4.5情景下,21世纪不同时期东部地区的积雪深度将会有所增加,北部和中部大部分地区在不同时期积雪深度将会变小;SSP3-7.0情景下,21世纪不同时期北部和西南地区的积雪深度将会普遍变小,东部地区的积雪深度将普遍增加;SSP4-3.4和SSP4-6.0情景下,21世纪不同时期西南昆仑山地区的积雪深度将会普遍变小,东部地区的积雪深度将普遍增加;SSP5-8.5情景下,北部阿尔泰山地区和东部地区的积雪深度将普遍增加。     

青藏高原气候变化的若干事实及其年际振荡的成因探讨

利用1961-2012年青藏高原88个气象台站逐月气温、降水以及温室气体等气候系统监测资料和CMIP5输出的未来气候变化情景数据,分析了近52年来青藏高原气候变化暖湿化的若干事实,揭示了其年际振荡与温室气体、高原加热场、高原季风、AO等气候系统因子的关系,预测了未来20~40年青藏高原可能的气候变化趋势。研究表明：近52年来青藏高原在总体保持气候变暖的趋势下自2006年以来出现了某些增暖趋于缓和的迹象,较全球变化滞后了8年左右;降水量的增加在青藏高原具有明显的普遍性和显著性,气候变湿较变暖具有一定的滞后性,降水量变化的5年短周期日趋不显著,而12年、25年较长周期逐渐明显且仍呈增多趋势。由于温室气体、气溶胶持续增加、高原夏季风趋强、ENSO事件和太阳辐射减少,青藏高原气候持续增暖但有所缓和;春季高原加热场增强、高原夏季风爆发提前且保持强劲,使得高原春、夏季和年降水量增加,而秋、冬季AO相对稳定少动,东亚大槽强度无明显变化,高原冬季风变化不甚显著,导致了高原秋、冬季降水量无明显变化。未来20~40年青藏高原仍有可能继续保持气温升高、降水增加趋势。     

Assessing the effects of the climate change on land cover changes in different time periods

The present research evaluated the relation between the normalized difference vegetation index (NDVI) changes and the climate change during 2000–2014 in Qazvin Plain, Iran. Daily precipitation and mean temperature values during 2015–2040 and 2040–2065 were predicted using the statistical downscaling model (SDSM), and these values were compared with the values of the base period (2000–2014). The MODIS images (MOD13A2) were used for NDVI monitoring. In order to investigate the effects of climate changes on vegetation, the relationship between the NDVI and climatic parameters was assessed in monthly, seasonal, and annual time periods. According to the obtained results under the B2 scenario, the mean annual precipitation at Qazvin Station during 2015–2040 and 2040–2065 was 6.7 mm (9.3%) and 8.2 mm (11.36%) lower than the values in the base period, respectively. Moreover, the mean annual temperature in the mentioned periods was 0.7 and 0.92 °C higher than that in the base period, respectively. Analysis of the correlations between the NDVI and climatic parameters in different periods showed that there is a significant correlation between the seasonal temperature and NDVI (P < 0.01). Moreover, the NDVI will increase 0.009 and 0.011 during 2015–2040 and 2040–2065, respectively.     

CMIP5多模式集合对南亚印度河流域气候变化的模拟与预估

利用印度河流域CRU、APHRODITE和CMIP5多模式逐月气温、降水格点数据集, 评估了CMIP5模式集合对印度河流域气候变化的模拟能力; 对多模式集合数据进行了偏差订正, 并对流域2046-2065年和2081-2100年气候变化进行了预估. 结果表明: 气候模式对流域年平均气温时间变化和空间分布特征有着较强的模拟能力, 时间空间相关系数均达到了0.01的显著性水平, 尤其对夏季气温的模拟要优于其他季节; 模式对降水的季节性波动也有着较好的模拟能力. 偏差订正后的预估结果表明, RCP2.6、4.5、8.5情景下, 相对于基准期(1986-2005年), 21世纪中期(2046-2065年)和末期(2081-2100年)整个流域年平均气温都有一定上升, 且流域上游增幅较大; 除RCP4.5情景下21世纪中期流域有弱减少趋势外, 年降水量都将有一定增长. 未来夏季持续升温将引起源区冰川的进一步消融, 春季降水对于中高海拔地区水资源的贡献将减弱; 流域北部高海拔区域冬季降水的增加有助冰川累积和上游水资源的增加, 东部高海拔区域冬季降水的减少会减少上游水资源. 两时期夏季降水都有一定的增长, 洪涝的发生风险加大; 流域暖事件和强降水事件也将可能增多.     

Application of Bias Correction and Spatial Disaggregation in Removing Model Biases and Downscaling over China

Global Climate Models (GCM) are the primary tools for studying past climate change and evaluating the projected future response of climate system to changing atmospheric composition. However, the state of art GCMs contain large biases in regional or local scales and are often characterized by low resolution which is too coarse to provide the regional scale information required for regional climate change impact assessment. A popular technique, Bias Correction and Spatial Disaggregation (BCSD), are widespreadly employed to improve the quality of the raw model output and downscaling throughout the world. Unfortunately, this method has not been applied in China. Consequently, the detailed principle and procedure of BCSD are introduced systematically in this study. Furthermore, the applicability of BCSD over China is also examined based on an ensemble of climate models from phase five of the Coupled Model Intercomparison Project (CMIP5), though the excellent performance of it has been validated for other parts of the world in many works. The result shows that BCSD is an effective, model independent approach to removing biases of model and downscaling. Finally, application scope of BCSD is discussed, and a suite of fine resolution multimodel climate projections over China is developed based on 34 climate models and two emissions scenarios (RCP4.5 and RCP8.5) from CMIP5.     

The distribution and abundance of chironomids in high-latitude Eurasian lakes with respect to temperature and continentality: development and application of new chironomid-based climate-inference models in northern Russia

The large landmass of northern Russia has the potential to influence global climate through amplification of climate change. Reconstructing climate in this region over millennial timescales is crucial for understanding the processes that affect the global climate system. Chironomids, preserved in lake sediments, have the potential to produce high resolution, low error, quantitative summer air temperature reconstructions. Canonical correspondence analysis of modern surface sediments from high-latitude lakes, located in northern European Russia and central Siberia, suggests that mean July air temperature is the most significant variable explaining chironomid distribution and abundance. This strong relationship enabled the development of a chironomid-based mean July air temperature-inference model based on 81 lakes and 89 taxa which has a r_jack² = 0.92 and RMSEP = 0.89 °C. Comparison of taxon responses to July temperature between this Russian and existing Norwegian data-sets shows that the temperature optima of individual taxa were between 1 and 3 °C higher in the Russian data regardless of modelling technique. Reconstructions based on fossil assemblages from a Russian tundra lake core (VORK5) using a Norwegian chironomid-based inference model provide mean July air temperature estimates that are 1.0–2.7 °C colder than from the 81-lake Russian model and are also lower than the instrumental record from a nearby meteorological station. The Norwegian model also did not reconstruct decadal-scale fluctuations in temperature seen in the instrumental record. These observations suggest that chironomid-based inference models should only be applied to sediment cores which have similar climate regimes to the geographic area of the training set. In addition a 149 lake, 120 taxa chironomid-based continentality inference model was also developed from the modern Norwegian and Russian training sets. A 2-component WA-PLS model was the minimal adequate model with r_jack² = 0.73 and RMSEP = 9.9 using the Gorczynski continentality index. Comparison of reconstructed continentality indices from the tundra lake, VORK5, show close agreement with local instrumental records over the past 70 years and suggest that the model is reliable. Recent warming in the Arctic has been spatially and seasonally heterogeneous; in many areas warming is more pronounced in the spring and autumn leading to a lengthening of the summer, while summer temperatures have remained relatively stable. A continentality inference model has the potential to detect these seasonal changes in climate.