Climate change in the Tianshan and northern Kunlun Mountains based on GCM simulation ensemble with Bayesian model averaging

Climate change in mountainous regions has significant impacts on hydrological and ecological systems. This research studied the future temperature, precipitation and snowfall in the 21^（st） century for the Tianshan and northern Kunlun Mountains（TKM） based on the general circulation model（GCM） simulation ensemble from the coupled model intercomparison project phase 5（CMIP5） under the representative concentration pathway（RCP） lower emission scenario RCP4.5 and higher emission scenario RCP8.5 using the Bayesian model averaging（BMA） technique. Results show that（1） BMA significantly outperformed the simple ensemble analysis and BMA mean matches all the three observed climate variables;（2） at the end of the 21^（st） century（2070–2099） under RCP8.5, compared to the control period（1976–2005）, annual mean temperature and mean annual precipitation will rise considerably by 4.8°C and 5.2%, respectively, while mean annual snowfall will dramatically decrease by 26.5%;（3） precipitation will increase in the northern Tianshan region while decrease in the Amu Darya Basin. Snowfall will significantly decrease in the western TKM. Mean annual snowfall fraction will also decrease from 0.56 of 1976–2005 to 0.42 of 2070–2099 under RCP8.5; and（4） snowfall shows a high sensitivity to temperature in autumn and spring while a low sensitivity in winter, with the highest sensitivity values occurring at the edge areas of TKM. The projections mean that flood risk will increase and solid water storage will decrease.

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

IAP GCM模式大气背景环流在厄尔尼诺年的异常

本文分析了中国科学院大气物理研究所大气环流模式(IAP GCM)模式大气5～9月平均环流(本文称为背景环流)。结果表明;厄尔尼诺年一系列重要系统(南方涛动、瓦克环流、哈德莱环流、西太平洋副热带高压和热带辐合带)及大范围降水均发生明显异常;北半球西太平洋热带、副热带是环流异常的主要区域。它们与观测资料的分析结果基本一致,从而论证了该模式在低纬环流研究中的应用前景。

基于GCM(1,N)自适应关联组合模型的PM_(2.5)浓度预测

PM_(2.5)浓度的变化与雾霾灾害天气的发生有着内在的必然联系,准确预测PM_(2.5)浓度变化趋势,对有效防治大范围雾霾灾害天气的发生具有重要指导作用。本研究根据PM_(2.5)浓度受多因素扰动的灰特性,采用等维灰递补的方法,及时补充新的灰信息,构建了PM2.5主影响因子灰关联计算模型;同时引入灰控制参数对GM(1,N)模型进行改进,满足多影响因素条件下的精确预测,将二者结合建立了适应于不同N元的GCM(1,N)自适应预测模型。通过对北京地区实测数据的应用和分析,GCM(1,N)计算预测模型精度达到89.75%~96.44%,PM_(2.5)浓度预测相对误差在7.32%~15.21%之间,取得了较好的预测效果。

气候变化情景下北江流域骤发干旱特征变化预测

以北江流域为研究对象,利用VIC(Variable Infiltration Capacity)模型与CMIP5全球气候模式耦合构建了流域水循环模型,基于模型输出的蒸发和潜在蒸发数据,构建基于SESR指数的骤发干旱(简称骤旱)识别方法,评估2021—2050年三种排放情景下(RCP2.6、RCP4.5、RCP8.5)骤旱特征(频次、历时、强度)相对于基准期(1971—2000)的变化及不确定性。结果表明,在RCP情景下:(1)流域呈持续增暖趋势,且排放情景越高升温幅度越大,降水、蒸发和潜在蒸发呈总体呈减小趋势,但潜在蒸发减小幅度小于蒸发;(2)骤旱频次在流域西部(东部)减少(增加),且增幅随排放情景上升而增大(<80%),流域东北部和南部预计会遭遇强度更高、历时更长的骤旱过程;(3)不同骤旱特征预测的不确定性差异较大,且均呈现出较强的空间异质性。

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Performance of a Reconfigured Atmospheric General Circulation Model at Low Resolution

Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model （GCM）, which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM （AGCM）, the Grid Atmospheric Model of IAP/LASG （Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics）, at low resolution （GAMIL-L, hereafter）, and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72 × 40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature （SST） forcing, and the other was a 50-yr （1950-2000） integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated.The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model （CAM2） physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.

Impacts of a GCM's Resolution on MJO Simulation

Long-term integrations are conducted using the Spectral Atmospheric Model （referred to as SAMIL）, which was developed in the Laboratory for Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics （LASG） in the Institute of Atmospheric Physics （IAP）, with different resolutions to inves-tigate sensitivity of the Madden-Julian Oscillation （MJO） simulations to the model＇s resolution （horizontal and vertical）. Three resolutions of the model, R15L9, R42L9 and R42L26, with identical physical processes, all produced the basic observed features of the MJO, including the spatiotemporal space-time spectra and eastward propagation. No fundamental differences among these simulations were found. This indicates that the model resolution is not a determining factor for simulating the MJO. Detailed differences among these modeling results suggest, however, that model resolution can substantially affect the simulated MJO in certain aspects. For instance, at a lower horizontal resolution, high frequency disturbances were weaker and the structures of the simulated MJO were better defined to a certain extent. A higher vertical resolution led to a more realistic spatiotemporal spectrum and spatial distribution of MJO precipitation. Meanwhile, increasing the model＇s resolution improved simulation of the climatology. However, increasing the resolution should be based on improving the cumulus parameterization scheme.

Climate Simulations Based on a Different-GridNested and Coupled Model

An atmosphere-vegetation interaction model (AVIM) has been coupled with a nine-layer General Cir culation Model (GCM) of Institute of Atmospheic Physics / State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/ LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. AVIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/ LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon gitude 7.5?and latitude 4.5? the vegetation is given a high resolution of 1.5?by 1.5?to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis.Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

多GCM模型集合下开都河流域未来气候变化预估

基于逐步聚类分析的统计降尺度模型(SCADS模型),在多GCM模型集合的9个大尺度气象变量与开都河流域6个气象变量之间,建立统计降尺度关系,并进行开都河流域未来气候变化的预估。结果表明,SCADS模型生成的开都河流域各气象变量的模拟值与实测值拟合较好。各气象变量在率定期(1961年-1990年)和验证期(1991年-1999年)的NSE系数均大于0.55,精度较高。此外,利用SCADS模型进行开都河流域各气象变量的预估。发现在三个不同时期内(2011年-2040年,2041年-2070年和2071年-2100年),月均气温升高,月均蒸发量、降水量、日照时数增加,月均相对湿度升高。

GCM预测模式下黑河流域潜在蒸散发的演变分析

以Penman-Monteith模型为基准,通过参数修正从7个温度类模型中优选出适用于黑河流域潜在蒸散发(PET)估算的最优模型,再根据CMIP5中CSIRO-Mk3.6.0气候模式输出的研究区未来气候情景数据,对黑河流域历史时期(1961-2015年)和未来2021-2050年(T1)、2051-2080年(T2)2个时段的PET值进行估算,并从时间和空间尺度2个方面分析其变化特征.结果表明:1)研究区气象数据资料缺乏时(例如仅有气温数据),参数修正后的Hargreaves-Samani模型可以作为Penman-Monteith的替代模型;2)黑河流域历史时期多年平均PET为1102 mm,空间上由上游向下游逐渐增加,与多年平均气温的空间分布具有较强的一致性;3)流域未来多年平均PET空间分布特征基本不变.受流域未来最高、最低气温增加的影响,流域多年平均PET在T1和T2时段较历史时期分别增加15%和20%.不同空间位置处,PET变化存在差异:T1时段中游酒泉站较历史时期有所下降,而其余站点则有所上升,T2时段所有站点较历史时期则均有上升;且未来2个时段流域上游PET增幅均大于流域下游,这种空间差异性与流域未来最高、最低气温变幅的空间差异性较为一致.

Seasonal Prediction Experiments of the Summer Droughts and Floods during the Early 1990′s in East Asia with Numerical Models

It has been shown by the observed data that during the early 1990′s, the severe disastrous climate occurred in East Asia. In the summer of 1991, severe flood occurred in the Yangtze River and the Huaihe River basin of China and in South Korea, and it also appeared in South Korea in the summer of 1993. However, in the summer of 1994, a dry and hot summer was caused in the Huaihe River basin of China and in R. O. K.. In order to investigate the seasonal predictability of the summer droughts and floods during the early 1990′s in East Asia, the seasonal prediction experiments of the summer droughts and floods in the summers of 1991-1994 in East Asia have been made by using the Institute of Atmopsheric Physics-Two-Level General Circulation Model (IAP-L2 AGCM), the IAP-Atmosphere/Ocean Coupled Model (IAP-CGCM) and the IAP-L2 AGCM including a filtering scheme, respectively. Compared with the observational facts, it is shown that the IAP-L2 AGCM or IAP-CGCM has some predictability for the summer droughts and floods during the early 1990′s in East Asia, especially for the severe droughts and floods in China and R. O. K.. In this study, a filtering scheme is used to improve the seasonal prediction experiments of the summer droughts and floods during the early 1990′s in East Asia. The predicted results show that the filtering scheme to remain the planetary-scale disturbances is an effective method for the improvement of the seasonal prediction of the summer droughts and floods in East Asia.

SEASONAL HEAT BUDGET IN THE TROPICAL WESTERN PACIFIC OCEAN IN A GLOBAL GCM I. GENERAL DESCRIPTION*

This paper describes the large scale aspects of the seasonal surface heat budget and discusses its main forcing mechanisms in the tropical Western Pacific Ocean. The high - resolution general circulation model (Semtner & Chervin, 1992) used in this study reproduced well the observed upper-layer thermal structure and circulation. It is shown that at least on the average of the study region (20 °N -20°N, west boundary-160 °E) the semiannual variation is a dominant signal for all heat budget components and is presumably due to the sun's passing across the equator twice a year; but that the components have substantial differences in amplitude. The local Ekman divergence in the region does not change significantly through the year. As a result, the change in surface heat content is roughly half due to ocean ?atmosphere heat exchange and half due to heat advection by remotely forced verti-cal motion. Horizontal currents do not play a significant role directly by advection, because the wat-er which enters the region is not very much different in temperature from the water which leaves it.

SEASONAL HEAT BUDGET IN THE TROPICAL WESTERN PACIFIC OCEAN IN A GLOBAL GCM Ⅱ. IN FIVE SUBREGIONS

The general features of the seasonal suuface heat budget in the tropical western Pacific Ocean,20°S-20°N, western boundary-160°E, were documented by Qu (1995) using a high-resolution generalcirculation model (GCM, Semtner & Chervin,1992) ard existing observations.Close inspection of thesmaller areas, with the whole region further partitioned into six parts, showed different mechanisms balancethe seasonal surface heat budget in different parts of the region The results of study on five subregionsare detailed in this article. In the equatorial (3°S - 3°N) aed North Equatorial Countercurrent(3°N-9°N) region, the surface the flux the does not change significantly throughout the year, so the surface heat content is determined largely by vertical motion near the equator and roughly helf due to horizontal and halfdue to vertical circulation in the region of the North Equatorial Countercurrent(NECC). In the othersubregions (9°N-20°N, 20°S -11°S aed 11°S -3°S ), however, in addition to ocean

Modelling Impacts of Climate Change on Maize (<i>Zea mays</i>L.) Growth and Productivity: A Review of Models, Outputs and Limitations

The use of crop modelling in various cropping systems and environments to project and upscale agronomic decision-making under the facets of climate change has gained currency in recent years. This paper provides an evaluation of crop models that have been used by researchers to simulate maize growth and productivity. Through a systematic review approach, a comprehensive assessment of 186 published articles was carried out to establish the models and parameterization features, simulated impacts on maize yields and adaptation strategies in the last three decades. Of the 23 models identified, CERES-maize and APSIM models were the most dominant, representing 49.7% of the studies undertaken between 1990 and 2018. Current research shows projected decline in maize yields of between 8% - 38% under RCP4.5 and RCP8.5 scenarios by the end of the 21st century, and that adaptation is essential in alleviating the impacts of climate change. Major agro-adaptation options considered in most papers are changes in planting dates, cultivars and crop water management practices. The use of multiple crop models and multi-model ensembles from general circulation models (GCMs) is recommended. As interest in crop modelling grows, future work should focus more on suitability of agricultural lands for maize production under climate scenarios.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.

Future meteorological drought conditions in southwestern Iran based on the NEX-GDDP climate dataset

Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts.Therefore,studying the future meteorological drought conditions at a local scale is vital.In this study,we assessed the efficiency of seven downscaled Global Climate Models(GCMs)provided by the NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP),and investigated the impacts of climate change on future meteorological drought using Standard Precipitation Index(SPI)in the Karoun River Basin(KRB)of southwestern Iran under two Representative Concentration Pathway(RCP)emission scenarios,i.e.,RCP4.5 and RCP8.5.The results demonstrated that SPI estimated based on the Meteorological Research Institute Coupled Global Climate Model version 3(MRI-CGCM3)is consistent with the one estimated by synoptic stations during the historical period(1990-2005).The root mean square error(RMSE)value is less than 0.75 in 77%of the synoptic stations.GCMs have high uncertainty in most synoptic stations except those located in the plain.Using the average of a few GCMs to improve performance and reduce uncertainty is suggested by the results.The results revealed that with the areas affected by wetness decreasing in the KRB,drought frequency in the North KRB is likely to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios.At the seasonal scale,the decreasing trend for SPI in spring,summer,and winter shows a drought tendency in this region.The climate-induced drought hazard can have vast consequences,especially in agriculture and rural livelihoods.Accordingly,an increasing trend in drought during the growing seasons under RCP scenarios is vital for water managers and farmers to adopt strategies to reduce the damages.The results of this study are of great value for formulating sustainable water resources management plans affected by climate change.

长江流域基于空间指标的GCMs模拟结果优选组合

提出一种针对长江流域全球气候模式(global climate models,GCMs)输出的降水及气温变量的优化组合方法。首先,利用7个空间指标对国际耦合模式比较计划第6阶段(couple model inter-comparison project phase 6,CMIP6)数据集的不同GCMs输出的降水量及最高、最低气温进行综合排序,并采用简单平均法、随机森林法对子流域及全流域的多GCMs组合进行排序,进而建立各变量GCMs优化组合。针对气候模式数据空间评价较少的问题,提出一种高精度的空间优化组合的融合方法,该方法将空间优化组合问题解耦为单模型排序和多GCMs优化组合的问题。在单模型排序后,基于当前排序结果构建一个组合优化问题,通过求解该问题得到模型优化组合。为GCMs提出了一种有效提高空间精度的融合方法,GCMs经随机森林法组合后对长江流域降水及气温空间模拟效果良好。

近50a来黄河上游水循环要素变化分析

根据水文、气象台站观测资料,分析了黄河上游有器测资料几十年来降水、温度、径流等水循环素的变化过程与特征。结果显示,温度近几十年来流域各个地方有着不同程度的上升,与全球变暖有着明显的对应关系;而随着气温的上升,蒸发和下渗呈增加的趋势。降水变化的区域性特征十分明显,降水量的增减随地理位置不同而差异较大。受主要产流区域降水减少,气温上升的影响,黄河上游产水量呈持续递减的态势。在上述分析基础上,利用全球气候模式(GCMs)与统计模式对未来流域降水和径流的可能变化进行了预测。结果表明,未来30 a里,随着温度将进一步上升,降水量将比目前有明显增加,黄河上游的径流量将随降水量的增加而进入一个相对丰水的时期。

青藏高原隆升与欧亚内陆及北非的干旱化

通过利用一个较为完善的大气环流模式（ＧＣＭ）进行了一系列青藏高原不断隆升的 数值模拟试验结果。共进行了１１个改变地形高度的数值试验，即对欧亚大陆上现代大地形所 在地区（约１０～６０°Ｎ，５０～１４０°Ｅ）陆地上所有格点的地形高度分别取为现代地形高度值的 １００％，９０％，８０％，７０％，…，１０％，外加一个无地形试验Ｍ００，共完成了１１个试验。结合与干旱 化有关的地质记录，探讨了高原隆起在欧亚内陆及北非干旱演化过程中的作用。结果表明，仅 仅改变高原地区地形高度的数值试验结果与气候变化地质记录在趋势上有可比性，青藏高原 隆升是中亚及北非地区在地质时间尺度上干旱化加剧的重要原因，但却不是上述干旱区形成 的根本原因。