② 中国科学院大学, 北京 100049;
③ 中国科学院青藏高原地球科学卓越创新中心, 北京 100101;
④ 中国科学院植物研究所, 北京 100093)
古气候要素的定量化一直是古气候学研究的核心目标之一,在认识过去气候变化规律和降低未来气候变化预估的不确定性中发挥重要的作用[1]。近半个世纪以来,古气候学家利用海洋、湖泊、黄土、冰芯、石笋和树轮等地质记录,成功实现了在构造、轨道、亚轨道时间尺度上全球重要区域和特征时段古气候要素的定量化重建[2~7]。这些成果,有力推动了我们对地球系统不同时间尺度气候变化过程的理解,加深了对气候变化动力机制的认识。
全新世中期时段(6±0.5ka14 C),由于当时全球冰量与现今相近,而夏季太阳辐射量比现在高,冬季太阳辐射量比现在低;因此,该时段是研究地球气候系统对太阳辐射季节性变化响应的特征时段,也是全球古气候重建和古气候模拟对比计划重点关注的典型时段之一[6, 8~11]。近年来,古气候定量化重建表明:在温度变化方面,全球平均温度比现在高约0.5℃[12, 13],但不同区域表现出明显的空间差异[6, 14]。在欧洲和非洲区域表现为较明显的增温,增温幅度达2~5℃[15~18],而在北美西部和西伯利亚南部区域则表现为较明显的降温,降温幅度为1~4℃[6, 18]。在降水变化方面,在欧洲、亚洲和北非区域表现为降水增加,增加约20~200mm[6, 18],而北美东部区域则表现为降水的减少,减少约50~150mm[6]。上述气候变化揭示,地球气候系统对季节性太阳辐射变化的响应具有明显的空间差异,且具有复杂性。因此,需大力加强不同区域气候的定量化重建,以更好揭示全新世中期气候变化特征及其驱动机制。
我国地处东亚季风区,其气候变化对理解东亚季风的演化历史具有重要的意义,因此备受古气候研究的关注。在这一领域,我国学者做了大量的工作,取得长足的进展。20世纪90年代初,Shi等[19]系统总结了前人的定量化成果,较早重建出全新世中期我国温度的空间格局。结果表明,我国南方增温约1~2℃,而北方增温达约3℃,尤其在青藏高原,增温幅度可达约4~5℃。之后,很多学者利用高分辨率的湖泊和黄土等沉积记录,通过花粉-气候转换函数[20~22]、气候-花粉响应面[23]、现代最佳类比[24]和共存分析[25]等古气候定量化方法,进一步重建了不同区域或点位的温度变化特征,揭示出全新世中期我国不同区域年均温可能存在从2.4℃降温到5.8℃增温的较大幅度变化。在降水量重建方面,全国整体表现为降水增加,空间变化范围在34mm降低至267mm增加之间。这些研究,增强了全新世中期时段我国区域气候空间格局变化的认识。
然而,上述古气候定量化重建结果与古气候模拟结果之间存在较大的差异[26]。在温度变化上,全新世中期我国年均温重建结果主要表现为升温;而模拟结果则表现为全国降温(约0.4℃),其中夏季增温约1℃,冬季降温约1.4℃[26]。在降水变化上,重建结果表现为全国降水的增加,而模拟结果则呈现西北和中部区域降水的减少[27]。对于上述分歧,其可能原因在于,生物气候指标所反映的是季节性气候条件,并非年均的气候状态[28]。由于以往定量重建方法难以有效区分季节性温度、降水和大气CO2浓度变化对植物生长的影响,导致重建结果可能存在一定的不确定性;因此,全面考虑气候季节变化和大气CO2等环境要素对植被生长的可能影响,更加可靠地重建古气候要素,尤其是季节性的气候变化特征,可能是解决上述分歧的关键[18, 29]。
本次研究,我们利用模拟植物生理过程基础上的植被反演方法[18, 29, 30],基于新完善的我国全新世中期孢粉生物群区化数据,实现古气候要素的定量化重建,获得我国上述特征时段的气候格局变化特征。
2 材料和方法 2.1 孢粉数据近年来,随着具准确定年、高分辨率孢粉记录的大量涌现,较高精度的我国区域气候环境格局重建成为可能。本研究在原有中国第四纪孢粉数据库[31]的基础上,对公开发表的末次盛冰期以来我国孢粉序列进行系统整理;选取孢粉谱清晰,剖面序列年代控制点大于3个,采样分辨率高于1000年,且避开人类遗址的点位。新增孢粉序列108点位(图 1),尤其在西北地区、青藏高原、黄土高原和南方地区,有效弥补了原我国第四纪孢粉数据库孢粉点位在上述区域较稀疏的不足。上述点位数字化孢粉序列103个,原始孢粉数据点位5个。到目前为止,我国第四纪孢粉数据库孢粉点位,全新世中期时段从原来110个增至218个,空间覆盖度有显著提高。在年代质量控制方面,根据Webb 1~7级标准[32],全新世中期时段约70 %的点位达到1级和2级,整体年代质量控制也有进一步提高。
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图 1 前人重建全新世中期温度和降水的变化 Fig. 1 Previous reconstruction of temperature and precipitation anomalies during the mid-Holocene in China |
本次利用植被反演方法开展古气候重建,是基于BIOME6000孢粉生物群区化方法[9]获得的定量化植被类型数据。尽管生物群区化可能掩盖了一些生物群区中植物种属类型变化的信息[33],但与孢粉种属相比,生物群区能很好地反映与气候变化之间的确定关系[34];并且,利用孢粉种属组合而成的生物群区数据,能一定程度上克服过去时段孢粉种属缺乏现代可类比的弱点[35],提高重建的可靠性;此外,利用这一标准化的孢粉数据定量化方法,使大区域尺度上获得植被的演化和古气候要素定量化重建成为了可能。此次研究,我们利用我国第四纪孢粉数据库中的生物群区化方案[36],实现全新世中期时段的植被类型定量化重建。
现代气候数据是来自国家气象局全国657个气象台站1951~2001年的月平均气候资料1) 基于上述气象台站数据,利用神经网络插值技术[37],获得各孢粉采样点的逐月气候要素。土壤质地数据来源于世界粮农组织的1 ︰ 5000000全球数字化土壤图[38]。全新世中期大气CO2浓度根据冰芯记录设定为270 ppmv[39]。
1) 中国气候局.中国地面气象记录月报. 1951~2001。
2.2 植被反演方法利用植被反演方法进行古气候要素定量化重建(图 2),其核心就是将植被模型BIOME4[40]与反演过程[29]相结合,获得孢粉数据所指示的植被类型生长的气候区间,进而实现过去气候要素的定量化重建。具体植被反演过程方法的描述详见吴海斌等[30]。
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图 2 植被反演方法重建古气候要素流程[30] Fig. 2 Schematic diagram of the inverse vegetation modelling approach for the palaeoclimatic reconstruction[30] |
由于植被的生长主要受控于气候条件,尤其是生物气候条件[40],如生物有效积温(GDD5)、最冷月温度(MTCO)、最热月温度(MTWA)和有效湿度(α);因此,基于植被反演方法,模拟输出上述生物气候要素,获得孢粉所指示植被类型的生物气候区间。此外,利用过去逐月气候信息,实现对年均温度和年降水量的定量化重建。模型模拟输入的气候要素变化区间见表 1,上述气候变化应该能较好涵盖全新世中期我国区域气候变化的可能范围。
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表 1 新世中期时段模型模拟输入气候参数相对于现代气候要素的变化区间 Table 1 The ranges of input climatic parameters for simulation during the mid-Holocene period |
利用植被反演新方法和新完善的中国第四纪孢粉数据库数据,我们定量化重建了全新世中期时段我国气候要素空间格局(图 3)。全国整体年均温比现在高约0.7℃;其中,西北地区和东部沿海比现在的略低,而东北、华中和华南地区则比现在高,尤其东北地区增温幅度可达3~5℃。在季节性变化方面,最冷月温度和最热月温度变化表现出较大的空间差异。全国平均最冷月温度比现在高约1℃,在我国北方区域有较显著的增温,而青藏高原则有所降温;最热月温度整体比现在高约0.5℃,但在西北区域有所降温。
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图 3 全新世中期我国温度和降水空间格局重建(相对现代,即1951~2001年平均气候的变化量) (a)年均温度变化;(b)最冷月温度变化;(c)最热月温度变化;(d)年降水量变化;(e)夏季降水变化 Fig. 3 Reconstruction of temperature and precipitation anomalies during the mid-Holocene in China from modern values(mean climate from 1951 to 2001A.D.).(a)Mean annual temperature; (b)Mean temperature of the coldest month; (c)Mean temperature of the warmest month; (d)Mean annual precipitation; (e)Summer precipitation |
在降水变化上,全新世中期我国年降水量整体比现在高约230mm(图 3d),其中东部地区增加显著,而西北地区则增加不明显。就季节降水变化而言,全国夏季降水比现在高约33 % (图 3e),其空间变化基本与年降水量变化一致,表明年降水量增加主要是夏季降水增加所导致。上述降水增加指示,全新世中期东亚夏季风强度有明显的增强。
4 讨论 4.1 与以往重建结果的对比本次研究,我们较系统收集和整理已发表的我国区域全新世中期气候要素的重建结果[41~146](表 2)。就整体而言,以往对我国全新世中期的古气候重建主要以定性为主,并指示当时气候比现在温暖湿润。在定量化重建方面,主要通过孢粉-气候的转换函数、最佳类比、趋势面分析和共存分析等统计学方法。结果表明,全新世中期年均温相对现在呈现整体增温(图 4a);其中,青藏高原增温幅度最大,达约4~5℃;我国北方区域增温约3℃;南方区域增幅较小,为约1℃。年降水量呈现增加趋势,全国平均增加约87mm(图 4c)。
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表 2 前人重建全新世中期温度和降水的变化 Table 2 Previous reconstruction of temperature and precipitation anomalies during the mid-Holocene in China |
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图 4 全新世中期本次温度和降水重建与以往重建的对比 (a)以往年均温度重建变化,菱形为定性重建结果,红色为增温,绿色为降温;圆形为定量重建结果;(b)本次年均温度重建变化;(c)以往年降水量重建变化,菱形为定性重建结果,绿色为降水增加,红色为降水减少;(d)本次年降水量重建变化 Fig. 4 Comparison between our climate reconstruction and previous reconstruction.(a)Previous temperature results. Diamond is the qualitative reconstruction, red is the temperature increase and green is the temperature decrease; Circle is quantitative reconstruction; (b)Mean annual temperature reconstruction in this study; (c)Previous precipitation results, diamond is the qualitative reconstruction, red is the precipitation increase and green is the precipitation decrease; Circle is quantitative reconstruction; (d)Mean annual precipitation reconstruction in this study |
本次基于植被反演方法的气候重建表明,在温度变化方面,全新世中期全国年均温度比现在高约0.7℃,与以往重建具有一定的可比性,该结果进一步确认了全新世中期我国增温的事实。然而,在温度变化空间格局方面,却与以往结果具有较大的差异,表现为我国西北区域降温(图 4b),而以往重建则为较明显的增温。在降水变化方面,全新世中期我国降水整体有较明显的增加(约230mm),增加幅度比以往重建结果(约87mm)大,且降水增加幅度呈现从东南向西北减少的趋势(图 4d)。此外,本研究我们重建了季节性温度和降水的空间变化特征,获得了季节性气候变化与年均气候的异同;而以往重建,对季节性气候要素重建少,难以揭示季节性气候变化特征。
上述定量化重建差异,其可能原因在于:在点位空间覆盖度方面,相对以往重建本次重建点位的空间覆盖度显著提高,因此可获得更加可靠的空间变化结果。在重建方法上,以往古气候重建方法是基于当前状况下的植被-气候空间分布,通过数理统计获得它们之间的关系[147]。因此,这些方法不能考虑其他环境要素(如季节性气候和大气CO2浓度变化)对过去时段植被生长的可能影响。
由于植被反演方法是基于现有植物生理过程基础上的植被模型——BIOME4[40],考虑了气候要素的季节性变化、大气CO2浓度对植物生长的影响;并且在反演过去植被过程中,该方法让气候要素的输入具有足够大的变化区间,大气CO2浓度(可从冰芯等记录中重建获得)作为一个输入参数,模拟孢粉所记录的生物群区类型,获得满足植被生长所需的气候状况,进而实现古气候要素的定量化重建[18, 29, 30, 148]。因此,相较以往的数理统计方法,植被反演新方法,可以在很大程度上考虑过去季节性气候和CO2变化对植被生长的影响,能有效提高气候重建的精度,同时,这一方法也使古气候重建从统计模型向机理过程模型迈出了重要的一步。
4.2 与古气候模拟结果的对比近年来,由于国际古气候模拟对比计划(PMIP)的实施,已开展了大量全新世中期时段古气候模拟工作[8, 11]。在东亚季风区,也获得了丰富的古气候模拟结果[26, 149]。结果表明,在降水变化方面,我国东部区域和青藏高原降水增加显著(图 5g),而在我国西北和中部区域降水可能略有减少。这一结果与本次定量化重建的我国降水空间变化具有较好的可对比性(图 5h),尤其在季节性降水方面,模拟和重建结果均揭示年降水量变化主要来源于夏季降水的增加,且在我国东部和青藏高原地区增加最为明显。但在年降水增加幅度上,模拟结果[149](约22mm)明显低于重建结果(约230mm)。上述结果表明,古气候模型对全新世中期时段我国季风区降水空间变化已具有一定的模拟能力,但在季风降水强度的增加方面还需进一步的加强。就已有模拟结果认为,季风降水的增强主要源于轨道强迫所导致的夏季经向温度梯度减少以及夏季东亚与邻近海域间热力对比的增大所致[149]。
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图 5 全新世中期本次气候重建与古气候模拟对比计划(PMIP)重建的对比 (a)PMIP模拟年均温度变化;(b)重建年均温度变化;(c)PMIP模拟冬季温度变化;(d)重建最冷月温度变化;(e)PMIP模拟夏季温度变化;(f)重建最热月温度变化;(g)PMIP模拟夏季降水变化;(h)重建夏季降水变化 Fig. 5 Comparison between our climate reconstruction with PIMP simulation results.(a)Mean annual temperature from PMIP; (b)Reconstructed mean annual temperature in this study; (c)Winter temperature from PIMP; (d)Reconstructed mean temperature of the coldest month in this study; (e)Summer temperature from PIMP; (f)Reconstructed mean temperature of the warmest month in this study; (g)Summer precipitation from PIMP; (h)Reconstructed summer precipitation in this study |
在温度变化方面,模拟结果[26]表明,我国全新世中期相对现在普遍降温,整体降温约0.4℃,呈现南方降温大而北方降温小的空间格局(图 5a);夏季温度表现为全国较显著的增温(约1℃),而冬季温度则表现为较明显的降温(约1.4℃)。我们的重建结果与模拟结果具有较大的差异:年均温重建结果表明,我国大部区域(除西北地区和东部沿海)为增温(图 5b),尤其东北地区增温最为显著,而模拟结果则表现为整体降温。在季节性温度变化上,虽模拟结果较好重现夏季温度在东北、中部和南方区域的增温[26];但西北区域,重建结果表现为降温,而模拟结果则表现为增温(图 5e和5f)。在冬季温度变化上,重建结果呈现较普遍的增温,而模拟结果表明为整体的降温[26](图 5c和5d)。上述差异表明,现有古气候模拟对东亚地区季节性温度变化的模拟与实际的地质记录还有较大的差距。
当然,相对以往重建与模式模拟结果,本次重建结果与模拟结果可对比性有进一步的增强,这一可对比性增强为利用大气动力模式揭示我国季风区气候变化的动力机制提供了可能。对于上述差异,一方面,可能与现有模式较低的空间分辨率有关,需耦合高分辨率的区域模式提高区域气候的重建能力[150, 151];另一方面,由于模式自身的限制,虽然模式能较好模拟出全新世中期太阳辐射的季节性变化会导致我国夏季增温和冬季降温[26],但是现有模式未能有效包括所有的地球系统气候变化过程[14, 152],从而导致模拟精度的降低。今后,加强过去不同时间和空间尺度上模式模拟与古气候重建结果的对比,增强模式在长时间尺度上的模拟能力,这可能是提高气候系统模式预测未来气候变化的关键。
5 结论古气候要素的定量化,是过去气候变化研究的难点和努力方向。以往研究,主要以定性为主,定量化相对较少。本次研究,我们利用考虑植物生理过程的新一代植被反演方法,该方法能有效考虑季节性温度、降水和大气CO2浓度等环境因子对植物生长的影响;结合新完善的中国第四纪孢粉数据库中的孢粉数据,孢粉点位从原先的110个增加至218个,定量化重建了我国全新世中期时段古气候要素空间变化特征。结果揭示,全新世中期时段,我国年均温度比现在略高约0.7℃,表现为东部区域增加,尤其是东北地区,而西北地区可能降温;全国最冷月温度增温较明显,达约1℃,而最热月温度增温较小,为约0.5℃。我国年降水量整体比现在多约230mm,其中夏季降水比现在高约33 %;年降水量增加主要是夏季降水增多所导致,并表现为东部地区增加显著。本次重建结果能较好地区分季节性温度和降水变化特征,增强了与古气候模式模拟结果的可对比性。全新世中期的气候重建结果指示,全球增温情形将有利于我国降水的增加,并可能导致季节性温度空间变化加大。
致谢: 在本次研究中,全新世中期时段110点位孢粉的生物群区化数据由中国第四纪孢粉数据库提供。本研究得到国家重点研发计划项目(批准号:2016YFA0600504)、国家自然科学基金项目(批准号:41572165、41430531、41125011和41472319) 和中国科学院战略性先导科技专项项目——应对气候变化的碳收支认证及相关问题(批准号:XDA05120700) 共同资助。感谢中国第四纪科学研究会的约稿,此文献给刘东生院士百年诞辰纪念。
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② University of Chinese Academy of Sciences, Beijing 100049;
③ CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101;
④ Institute of Botany, Chinese Academy of Sciences, Beijing 100093)
Abstract
Knowledge of quantitative palaeoclimates is a crucial for the evaluation of climate changes for the earth system. Previous quantitative palaeoclimate reconstruction in China generally used the modern statistic methods between pollen and climate data. The reconstruction methods are built upon the assumption that plant-climate interactions remain the same through time, and implicitly assume that these interactions are independent of changes in the seasonal climate and the atmospheric CO2. This assumption may lead to a considerable bias. In this study, an improved inverse vegetation model that based on a physiological process has been designed to quantitatively reconstruct past climates, with a new China Quaternary Pollen Database. During the mid-Holocene period, mean annual temperature in China were higher ca.0.7℃ than present, especially in the Eastern China, but cooler in the northwest China. Winter temperature were generally higher ca.1.0℃ than today, but summer temperature only higher ca.0.5℃ than present. Mean annual precipitation were wetter ca.230mm than today, especially in the Eastern China, which was due to the increase of summer rainfall. Our results suggest that the precipitation maybe increase, while the seasonal temperature variation became significant with the global temperature warming. The new reconstructions therefore give a better agreement with PMIP simulations.