基于分位数映射法的黑河上游气候模式降水误差订正

区域气候模式降水弥补了高寒山区气象站点稀少的缺陷,是水文模拟的重要驱动变量。然而,高寒山区模式输出降水的总量和频率都存在较大不确定性。因此,改进了用于降水频率纠正的分位数映射法(Quantile Mapping,QM),对中尺度数值预报模式(Weather Research and Forecasting model,WRF)模拟的黑河上游日降水输出数据进行误差订正。选取第95分位和第98分位降水量为阈值,选择2004-2009年为建模时段,2010-2013年为验证时段,使用分段拟合的方法建立传递函数,侧重于对极端降水进行单独订正。研究结果表明:该方法不仅对降水空间分布有明显的改善,对极端降水也有很好的订正效果。订正前模式模拟日降水与台站之间的均方根误差为3.41 mm·d^-1,绝对偏差为115.67 mm·y^-1,订正后均方根误差减少为3.11 mm·d^-1,绝对偏差有明显改善,为60.3 mm·y^-1。订正后流域内年降水空间分布更加合理,年降水量也更接近于观测降水插值结果,其空间相关系数由0.74改善为0.94。春、夏季订正效果优于秋、冬季,其中夏季订正效果较为明显,订正前降水偏差百分比在-0.1~0.1以内的区域面积仅占流域总面积的28%,而订正后占比增加至66%。同时,该方法对极端降水有较好的订正效果,减小了日降水强度(SDII)和极强降水量(R99p)的模拟偏差,订正后的第95分位模拟降水与观测降水插值的相关系数由0.15提高到0.48。本研究为站点稀少的黑河上游提供了一种更有效的误差订正方案,有利于为寒区水文研究获取更精确的降水数据。     

长江流域气候变化高分辨率模拟与RCP4.5情景下的预估

基于长江流域142个气象站1986—2005年月降水和气温数据,评估由MPI-ESM-LR模式驱动的CCLM区域气候模式对长江流域气温和降水的模拟能力,并采用EDCDF法对气温和降水预估数据进行偏差校正。结果表明：该区域气候模式能较好地模拟出长江流域平均气温的季节变化和空间分布特征,但模拟值无论在季节还是年际尺度上均高于观测值。对降水而言,该模式不能较好地模拟出降水的季节分布特征,导致春季、冬季及年模拟值高于观测值,而夏季和秋季模拟值低于观测值。总体而言,该模式对气温的模拟效果相对较好。偏差校正后的预估结果表明：在RCP4.5情景下,长江流域未来（2016—2035年）平均气温相对于基准期（1986—2005年）将升高0.66℃,年降水量将减少2.2%。     

An inter-comparison of regional climate models for Europe: model performance in present-day climate

The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.     

欧亚环流异常对中国夏季降水的影响及其预测研究

文中利用奇异值分解 (SVD)方法 ,分析了 5 0 0hPa环流与中国降水的耦合作用。结果表明 ,夏季高度场和降水场相互的空间分布与大气环流的遥相关型紧密联系 ,所对应的时间系数对夏季旱涝趋势有较好的表征能力。冬、春季高度场和夏季降水场的相互关系显示出与夏季相类似的遥相关分布型。利用高度场与降水场奇异值分解的结果及前期环流异常信息 ,可以为夏季降水趋势预测提供参考     

中国当代土地利用变化对黄河流域径流影响

使用区域气候模式(RegCM3)和大尺度汇流模型(LRM),研究中国地区土地利用/植被覆盖变化对黄河流域降雨径流过程的影响。RegCM3嵌套于欧洲数值预报中心(ECMWF)再分析资料ERA40,分别进行了中国区域在实际植被和理想植被分布情况下两个各15年(1987～2001年)时间长度的积分试验。随后,RegCM3 两个试验的输出径流结果分别用来驱动LRM。与观测资料的对比分析表明,在实际土地利用状况下,LRM能较好地模拟黄河河川径流的季节和年际变化。研究结果指出,当代土地利用引起了冬季黄河上游部分地区降水减少,中下游地区降水增加;引起夏季整个黄河流域降水的减少。总体来说,当代土地利用变化引起黄河流域年平均降水的减少。对于水文站河川径流量,除了冬春季略有增加外,其他月份河川径流均会减少,并且在9月减少最多。土地利用引起的植被退化造成黄河径流的大幅度减少,并且越向下游减少幅度越大,这可能是引起黄河下游断流的重要原因之一。     

THE RELATIONSHIP OF THE PRECEDING WINTER MJO ACTIVITIES AND THE SUMMER PRECIPITATION IN YANGTZE-HUAIHE RIVER BASIN OF CHINA

The first two series(RMM1 and RMM2) of RMM Index(all-Season Real-time Multivariate MJO Index) are computed to obtain the interannual variation of the preceding winter(preceding December to current February) MJO strength,according to which active(or inactive) years of preceding winter MJO are divided.By utilizing the data provided by NCEP/NCAR,CMAP and China’s 160 stations from 1979 to 2008,we studied the preceding winter MJO strength and discovered that the summer precipitation in the basin are of significantly negative correlation,i.e.when the preceding winter MJO is relatively active,the summer precipitation in the basin decreases,and vise verse.We also analyzed the causes.When the preceding winter MJO is relatively active,its release of potential heat facilities Inter-Tropical Convergence Zone(ITCZ) to strengthen and locate northward in winter and propagate northeastward.This abnormal situation lasts from winter to summer.In mid-May,ITCZ jumps northward to the South China Sea,the western Pacific subtropical high withdraws eastward,and the South China Sea summer monsoon sets off and strengthens.In summer,ITCZ propagates to South China Sea-subtropical western Pacific,the zonal circulation of subtropical Pacific strengthens,and a local meridional circulation of the South China Sea to the basin area forms,giving rise to the East Asia Pacific teleconnection wave-train.An East Asian monsoon trough and the Meiyu front show opposite features from south to north,the East Asian summer monsoon strengthens and advances northward.As a result,the summer monsoon is weakened as the basin is controlled by the subtropical high continually,with less rain in summer.On the contrary,when the preceding winter MJO is inactive,ITCZ weakens and is located southward,the subtropical high is located southward in summer,and the basin is in a region of ascending airflow with prevailing southwest wind.The East Asian monsoon trough and EASM weaken so that summer monsoon is reduced in the basin where precipitation increases.     

2016年梅汛期降雨环流特征及ECMWF中期预报偏差分析

利用NCAR/NCEP逐日再分析资料和台站观测日平均降雨资料,分析2016年梅汛期的大气环流演变特点和期间3次强降雨过程的环流特征,对比了欧洲中期数值模式(EC模式)的预报能力,并对其中期预报降雨的落区偏北、强度偏弱的偏差原因进行分析。结果表明,2016年梅汛期中高纬度环流多变化,多冷空气活动但势力总体不强,夏季风在6月下旬和7月上旬逐步增强,西太平洋副热带高压稳定维持,为强降雨的发生提供了有利动力和水汽条件。在梅汛期前期EC在中期时效对于夏季风的预报强度偏强、副高位置偏北,直接造成模式预报的雨带位置偏北。EC对于乌拉尔山一带的环流系统预报能力较好,但对于日本海-鄂霍茨克海一带的环流系统预报能力较差,从而使得影响我国的冷空气路径和强度预报均出现偏差,这对于7月初的强降水的强度和落区预报也有明显影响。      

Numerical Simulation of Long-Term Climate Change in East Asia

A 10-yr regional climate simulation was performed using the fifth-generation PSU/NCAR Mesoscale Model Version 3 (MM5V3) driven by large-scale NCEP/NCAR reanalyses. Simulations of winter and summer mean regional climate features were examined against observations. The results showed that the model could well simulate the 10-yr winter and summer mean circulation, temperature, and moisture transport at middle and low levels. The simulated winter and summer mean sea level pressure agreed with the NCAR/NCEP reanalysis data. The model could well simulate the distribution and intensity of winter mean precipitation rates as well as the distribution of summer mean precipitation rates, but it overestimated the summer mean precipitation over North China. The model's ability to simulate the regional climate change in winter was superior to that in summer. In addition, the model could simulate the inter-annual variation of seasonal precipitation and surface air temperature. Geopotential heights and temperature at middle and high levels between simulations and observations exhibited high anomaly correlation coefficients. The model also showed large variability to simulate the regional climate change associated with the El Nino events. The MM5V3 well simulated the anomalies of summer mean precipitation in 1992 and 1995, while it demonstrated much less ability to simulate that in 1998. Generally speaking, the MM5V3 is capable of simulating the regional climate change, and could be used for long-term regional climate simulation.     

基于NCEP CFSv2模式的黑龙江省夏季降水预测研究

基于1982-2017年NCEP_CFSv2（NCEP Climate Forecast System version 2）模式预测资料对黑龙江省夏季降水进行降尺度预测。通过分析黑龙江省夏季降水与同期环流因子的关系、模式对关键区环流因子的预测,选取模式模拟与再分析资料相关较好、黑龙江降水实况与再分析资料关系较好的环流因子作为预测因子,结合最优子集回归法筛选因子,建立降尺度预测模型,最后采用交叉检验法进行预测效果检验和独立样本预测。结果表明：模式降尺度预测与实况的距平符号-致率为69%,6 a独立样本预测中有5 a预测正确,优于目前的业务预测效果。进-步研究发现,在模式能够准确预测环流因子的情况下,模式降尺度可以较好地预测黑龙江省夏季降水的趋势。此外,模式降尺度在拉尼娜年预测效果较好。     

耦合模式FGOALS-s2海洋同化试验模拟的西北太平洋海气相互作用特征

观测发现,西北太平洋区域夏季降水—SST存在显著的负相关,主要是由于El Ni?o衰减年西北太平洋异常反气旋持续至夏季,该过程是检验耦合模式性能的重要参照标准。本文利用中国科学院大气物理研究所近期气候预测系统IAP-DecPreS,通过海洋同化试验、大气模式AMIP试验与观测结果的比较,评估海洋同化试验对西北太平洋夏季局地海气相互作用特征的模拟影响。结果表明,海洋同化试验能够模拟出西北太平洋区域夏季降水—SST负相关,但负相关区域范围偏小。其与观测之间的最大差异出现在8月,西北太平洋负降水异常及异常反气旋位置偏东,强度偏弱。这是由于其模拟的El Ni?o衰减年夏季赤道东印度洋正降水异常偏弱且移动至赤道南侧,对流层增温偏弱,对西太平洋的遥相关作用偏弱。AMIP试验未考虑大气对海洋的反馈作用,不能再现西北太平洋降水—SST负相关,无法模拟出El Ni?o衰减年夏季西北太平洋异常反气旋。研究表明,海洋同化试验对西北太平洋区域局地海气相互作用特征的模拟能力较AMIP试验有所提升,其对8月西北太平洋降水与环流场的模拟偏差与东赤道印度洋降水模拟偏差有关。     

Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions

 Nested limited-area modelling is one method of down-scaling general circulation model (GCM) climate change simulations. To give credibility to this method the nested limited-area model (LAM) must be shown to simulate local present-day climate conditions fairly accurately. Here seven different European limited-area models driven by observed boundary conditions (operational weather forecast analyses) are validated against observations, and inter-compared for summer and winter months. Relatively large biases are found. In summer large positive surface air temperature biases are found over southeast Europe. The main reason is deficiencies in the surface hydrological schemes causing an unrealistic drying of the soil. In at least one of the models, most likely several of them, an additional factor is an overestimation of incoming solar radiation. Apart from excessive precipitation in mountainous areas in some models they generally show a negative bias due to the drying and decreased advection from the Atlantic. In winter most models have a positive precipitation bias which seems to be caused by an enhancement of advection from the Atlantic and enhanced cyclone activity. Surface air temperature biases are negative probably due to an underestimation of the incoming longwave radiation. Received: 11 December 1996 / Accepted: 17 March 1997     

Analysis of precipitation extremes in an ensemble of transient regional climate model simulations for the Rhine basin

A non-stationary index-flood model was used to analyse the 1-day summer and 5-day winter precipitation maxima in the Rhine basin in an ensemble of 15 transient regional climate model (RCM) simulations. It is assumed that the seasonal precipitation maxima follow a generalized extreme value (GEV) distribution with time varying parameters. The index-flood assumption implies that the dispersion coefficient (the ratio of the scale and the location parameters) and the shape parameter are constant over predefined regions, while the location parameter varies within these regions. A comparison with the estimates from gridded observations shows that these GEV parameters are too large in the summer season, while there is a large overestimation of the location parameter and underestimation of the dispersion coefficient in winter. However, a large part of the biases in the summer season might be due to the low number of stations used for gridding the observations. Though there is considerable variation in the changes of the extreme value distributions among the RCM simulations, common tendencies can be identified. In summer, large quantiles increase as a consequence of an increase of the dispersion coefficient, while there is almost no change of low quantiles. In winter, low quantiles increase because of an increase of the location parameter. This effect is, however, counterbalanced by a decrease of the shape parameter in most RCM simulations, resulting in only a slight increase of large quantiles. Departures from the assumed index-flood model were observed in the Alpine region in the south of the basin. This is due to the strong spatial heterogeneity in the dispersion coefficient in a number of RCM simulations and a significant altitude dependence of the trend in the location parameter in winter in five RCM simulations.     

SST and circulation trend biases cause an underestimation of European precipitation trends

Clear precipitation trends have been observed in Europe over the past century. In winter, precipitation has increased in north-western Europe. In summer, there has been an increase along many coasts in the same area. Over the second half of the past century precipitation also decreased in southern Europe in winter. An investigation of precipitation trends in two multi-model ensembles including both global and regional climate models shows that these models fail to reproduce the observed trends. In many regions the model spread does not cover the trend in the observations. In contrast, regional climate model (RCM) experiments with observed boundary conditions reproduce the observed precipitation trends much better. The observed trends are largely compatible with the range of uncertainties spanned by the ensemble, indicating that the boundary conditions of RCMs are responsible for large parts of the trend biases. We find that the main factor in setting the trend in winter is atmospheric circulation, for summer sea surface temperature (SST) is important in setting precipitation trends along the North Sea and Atlantic coasts. The causes of the large trends in atmospheric circulation and summer SST are not known. For SST there may be a connection with the well-known ocean circulation biases in low-resolution ocean models. A quantitative understanding of the causes of these trends is needed so that climate model based projections of future climate can be corrected for these precipitation trend biases.     

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.     

基于MTM-SVD方法的黄河流域夏季降水年际变化及其主要影响因子分析

应用中国气象台站积雪日数资料和NCEP/NCAR再分析资料以及多锥度—奇异值分解方法 (MTM-SVD),分析了近50年来黄河流域夏季降水的时空变化及其影响因子.发现黄河流域夏季降水存在显著的2～3年周期.在准3年周期上黄河流域夏季降水对前冬青藏高原东部积雪日数有很好的响应,当前冬高原积雪日数以正 (负) 异常为主时,接下来的夏季黄河流域降水偏少 (多).这种响应存在年代际变化,在1983年之前最为明显,1983~1993年是个调整时期,1993年以后又开始明显.在准2年周期上黄河流域夏季降水对前冬西太平洋暖池SST有很好的响应,当前冬西太平洋暖池SST偏高 (低) 时,接下来的夏季黄河流域降水表现为东多 (少)西少 (多) 型.这一响应同样存在年代际变化.前冬高原积雪和西太平洋暖池SST是影响黄河流域夏季降水的重要因子.     

Impact of Climate Change on Hydrological Regimes and Water Resources Management in the Rhine Basin

The International Commission for the Hydrology of the Rhine basin (CHR) hascarried out a researchproject to assess the impact of climate change on the river flow conditionsin the Rhine basin. Along abottom-up line, different detailed hydrological models with hourly and dailytime steps have beendeveloped for representative sub-catchments of the Rhine basin. Along atop-down line, a water balancemodel for the entire Rhine basin has been developed, which calculates monthlydischarges and which wastested on the scale of the major tributaries of the Rhine. Using this set ofmodels, the effects of climatechange on the discharge regime in different parts of the Rhine basin werecalculated using the results ofUKHI and XCCC GCM-experiments. All models indicate the same trends in thechanges: higher winterdischarge as a result of intensified snow-melt and increased winterprecipitation, and lower summerdischarge due to the reduced winter snow storage and an increase ofevapotranspiration. When the resultsare considered in more detail, however, several differences show up. These canfirstly be attributed todifferent physical characteristics of the studied areas, but different spatialand temporal scales used in themodelling and different representations of several hydrological processes(e.g., evapotranspiration,snow melt) are responsible for the differences found as well. Climate changecan affect various socio-economicsectors. Higher temperatures may threaten winter tourism in the lower wintersport areas. The hydrologicalchanges will increase flood risk during winter, whilst low flows during summerwill adversely affectinland navigation, and reduce water availability for agriculture and industry.Balancing the required actionsagainst economic cost and the existing uncertainties in the climate changescenarios, a policy of `no-regretand flexibility' in water management planning and design is recommended, whereanticipatory adaptivemeasures in response to climate change impacts are undertaken in combinationwith ongoing activities.     

基于降水遥相关型的夏季降水模式预测改进研究

我国月—季降水分布在空间上存在类似于大气环流遥相关的空间遥相关型。本文基于中国近57年夏季降水资料研究了我国夏季降水空间遥相关型的主要空间模态特征及其年代际变化,评估并改进了BCC_CSM模式、ECMWF_SYSTEM4模式以及NCEP_CFSV2模式对中国夏季降水的预测能力。研究结果显示,中国夏季降水实况中存在华北—长江下游、华东—中国中北部、华南—长江流域、西南—东北中部等4类显著的空间遥相关型。动力模式可以预测大尺度的降水分布,而对于不同区域之间降水遥相关这种雨带细节特征的预测能力则较为薄弱,存在着较多虚假相关。为改善模式降水预测技巧,以实况中的降水遥相关型作为约束条件构建了修正方案,以此来修正模式中的降水遥相关型分布。结果显示,经过修正能够有效地改善模式对东北中部、长江下游的预测能力,4年的回报检验结果显示,模式预测的平均距平一致率从47%提高为58%;平均均方根误差从153 mm减小为120 mm;平均趋势异常综合检验（PS）评分从64提高为73。     

The impact of climate change on the river rhine: A scenario study

This paper concerns the impact of human-induced global climate change on the River Rhine discharge. For this purpose a model for climate assessment, named ESCAPE, is coupled to a water balance model, named RHINEFLOW. From climate scenarios, changes in regional annual water availability and seasonal discharge in the River Rhine Basin are estimated. The climate scenarios are based on greenhouse gases emissions scenarios. An assessment is made for best guess seasonal discharge changes and for changes in frequencies of low and high discharges in the downstream reaches of the river. In addition, a quantitative estimation of the uncertainties associated with this guess is arrived at.The results show that the extent and range of uncertainty is large with respect to the best guess changes. The uncertainty range is 2–3 times larger for the Business-as-Usual than for the Accelerated Policies scenarios. This large range stems from the doubtful precipitation simulations from the present General Circulation Models. This scenario study showed the precipitation scenarios to be the key-elements within the present range of reliable climate change scenarios.For the River Rhine best guess changes for annual water availability are small according to both scenarios. The river changes from a present combined snow-melt-rain fed river to an almost entirely rain fed river. The difference between present-day large average discharge in winter and the small average discharge in autumn should increase for all scenarios. This trend is largest in the Alpine part of the basin. Here, winter discharges should increase even for scenarios forecasting annual precipitation decreases. Summer discharge should decrease. Best guess scenarios should lead to increased frequencies of both low and high flow events in the downstream (Dutch) part of the river. The results indicate changes could be larger than presently assumed in worst case scenarios used by the Dutch water management authorities.     

辐射参数化方案对气候模拟和回报的影响

研究两种不同辐射参数化方案(Morcrette 方案和Ritter方案)对一个大气环流模式及其与一个海洋环流模式的耦合模式的模拟和回报效果的影响. 大气模式的模拟结果表明,采用Morcrette方案模拟的降水较采用Ritter方案有明显改进.采用Morcrette辐射方案的大气模式对夏季500 hPa高度场的模拟比采用Ritter方案的大气模式有明显改进,但对冬季500 hPa高度场的模拟没有改进.大气-海洋耦合模式的20年夏季回报结果表明采用Morcrette方案回报的夏季降水在华北和江淮地区明显比采用Ritter辐射方案好;对于夏季温度,带有Morcrette方案的耦合模式的回报在江淮地区没有带有Ritter方案的耦合模式好,但在黄河以北和新疆等地区,前者明显好于后者.     

年际增量方法在西南夏季降水预测中的应用

利用中国西南地区80站逐月降水资料及NCEP/NCAR再分析资料等,采用降水预测新方法——年际增量法,考察影响中国西南地区夏季降水年际增量的前期冬、春季大气环流年际增量状况,并选取5个关键影响因子,采用多元回归法建立中国西南夏季降水年际增量预测模型。对降水年际增量进行预测,在1971—2010年的建模阶段,预测模型的拟合率为0.78,在2011—2017的后报检验7年中,有6年与实况值同位相。后报检验2011—2017年的降水距平百分率,均方根误差为16%。为考察对降水异常分布型的预报效果,逐站建立回归方程,并进行趋势预报检验,近5年的趋势异常综合评分高于发布预测,预报效果较好。因此,该方法的应用及模型的建立对提高西南地区夏季降水预测水平有重要意义。