土壤湿度年际异常对中国春、夏季气候模拟的影响

基于NCAR大气模式CAM3.1模式,设计了有、无土壤湿度年际异常两组试验对中国区域近40a(1961-2000年)气候进行了模拟。从气候态和年际变率的角度,通过分析两组试验的差值场来探讨土壤湿度年际异常对气候模拟的影响,并初步探讨了影响的可能机制。结果表明:模式模拟的温度和降水对土壤湿度的年际异常非常敏感,土壤湿度的年际变化对中国春夏季气候及其年际变率均有显著影响。当不考虑土壤湿度年际异常时,模式模拟的春夏季平均温度、最高温度、最低温度在我国大范围内降低,春夏季降水在东部大部分地区明显减少,西部增加。而模式模拟的春夏季温度、降水年际变率在中国大部分地区减弱。但当考虑土壤湿度的年际变化,则能在一定程度上提高模式对气候年际变率的模拟能力。在进一步分析表明土壤湿度年际异常时,主要通过改变地表能量通量和环流场,对温度、降水产生影响。当不考虑土壤湿度年际异常时,地表净辐射通量减少,地表温度降低,感热通量减少。感热通量差值场的空间变化和温度差值场的空间变化一致,感热通量对温度有一定影响。而潜热通量差值场的空间变化和降水的差值场的空间变化一致,可见降水受地表潜热通量的影响。土壤湿度年际异常引起的环流场的变化也是导致气候变化的原因之一,地表能量和环流场年际变率的改变对春夏季气候年际变率存在一定影响。     

Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon

We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6, respectively) in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period1979–2005. All 92 models are able to simulate the geographical distribution of the above variables reasonably well.Compared with earlier CMIP5 models, current CMIP6 models have nationally weaker cold biases, a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient, a comparable overestimation of the spatial variability of the interannual variability, and a similar underestimation of the strength of winter monsoon over northern Asia. Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon. The ability of models relates to their horizontal resolutions in certain aspects. Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.     

Customization of regional climate model (RegCM4) over Indian region

The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.     

土壤湿度年际变化对中国区域极端气候事件模拟的影响研究Ⅱ.敏感性试验分析

利用NCARCAM3.1大气环流模式,设计了有、无土壤湿度年际异常的两组数值试验,探讨了土壤湿度年际异常对极端气候事件模拟的可能影响。结果表明,模式模拟的极端气候事件对土壤湿度异常十分敏感,土壤湿度异常对极端气候指标的多年平均空间分布、年际变率以及年际变化均具有重要影响。当不考虑土壤湿度的年际异常时:(1)模拟的暖夜日数、暖昼日数和热浪持续指数的发生频次在全国范围内均明显减少,而霜冻日数则明显增加。极端降水指标的响应表现出明显的空间差异,极端降水频次在江淮流域明显减小,而极端降水强度则表现为东北减弱、长江流域增强;中雨日数和持续湿期在我国大部分地区减少。(2)极端气温指标的年际变率在我国大部分地区呈减小趋势;而极端降水事件的变化则较为复杂,极端降水频次和极端降水强度的年际变率在长江以南有所增强,而北方地区则有所减弱。中雨日数和持续湿期的年际变率在我国呈现出较为一致的减少趋势。(3)模式对暖夜日数、霜冻日数的年际变化的模拟能力明显下降,并对4个极端降水指标的年际变化的模拟能力在全国多数区域均有不同程度的下降。     

Evaluation of Total Precipitable Water from CRCM4 using the NVAP-MEaSUREs Dataset and ERA-Interim Reanalysis Data

The fourth-generation Canadian Regional Climate Model’s (CRCM4) precipitable water is evaluated and compared with observational data and ERA-Interim reanalysis data over five Canadian basins with simulations driven by ERA-Interim (two) and global climate models (two). Considering the 22 years of data available in the observations, we analyze precipitable water’s behaviour through its annual cycle, its daily distribution, and its annual daily maxima. For the simulations driven by reanalyses, differences in annual daily maximum values and their correlations with observations are examined. In general, the values for precipitable water simulated by CRCM4 are similar to those observed, and the model reproduces both the interannual and inter-basin variabilities. The simulation at 15 km resolution produces higher extreme values than simulations performed at 45 km resolution and higher than the observations taken at coarser resolution (1°), without much influence on the mean behaviour. Some underestimation is found with the simulation driven by the Canadian Centre for Climate Modelling and Analysis Model, version 3, a sign of a cold and dry bias, whereas the run driven by the European Centre Hamburg Model, version 5, is much closer to the observations, pointing to the importance of closely considering the regional–global model combination. Overall, CRCM4's ability to reproduce the major characteristics of observed precipitable water makes it a possible tool for providing precipitable water data that could serve as a basis for probable maximum precipitation and probable maximum flood studies at the basin scale.     

雅鲁藏布江流域夏季降水的年际变化及其原因

本文通过多套观测与再分析降水资料的比较,分析了雅鲁藏布江流域夏季降水的特征,从水汽含量与水汽输送的角度检验了雅鲁藏布江水汽通道的特点,研究了流域夏季降水的年际变化及其原因。分析表明:（1）该流域夏季降水大值位于雅鲁藏布江出海口至大峡谷一带,观测中流域平均降水可达5.8 mm d-1。不同资料表现的降水空间分布一致,但再分析降水普遍强于观测,平均为观测的2倍左右。（2）该流域夏季的水汽主要来自印度洋和孟加拉湾的偏南暖湿水汽输送,自孟加拉湾出海口沿布拉马普特拉河上溯至大峡谷,即雅鲁藏布江水汽通道。水汽收支诊断表明,夏季流域南部（即水汽通道所在处）是水汽辐合中心,流域平均的辐合约9.5 mm d-1,主要来自风场辐合与地形坡度的贡献。（3）不同再分析资料表现的流域降水和水汽分布特征总体一致,但量值差异较大。NCEP（美国国家环境预报中心）气候预报系统再分析资料CFSR、日本气象厅再分析资料JRA-25较欧洲中期天气预报中心再分析ERA-Interim资料更适于研究该流域（青藏高原东南部）的水汽特征,因为后者给出的流域降水和水汽偏强。（4）近30年该流域夏季降水无显著趋势,以年际变率为主。年际异常的水汽辐合（约为气候态的35.4%）源自异常西南风导致的局地水汽辐合（纬向、经向辐合分别贡献了16.5%、83.5%）,地形作用很小。流域夏季降水的年际变化是由印度夏季风活动导致的异常水汽输送造成的,其关键系统是印度季风区北部的异常气旋（反气旋）式水汽输送。     

高分辨率MRI模式对青藏高原夏季降水及水汽输送通量的模拟

本文使用MRI模式在不同分辨率下(180 km、120 km、60 km、20 km)的AMIP试验结果, 分析了该模式对青藏高原夏季降水及水汽输送通量的模拟, 并考察模式分辨率的影响。结果表明:MRI模式能够较为合理地模拟出青藏高原夏季气候平均的降水空间分布, 但对气候平均水汽输送通量以及降水年际变化的模拟却存在较大的误差。随着分辨率的提高, 该模式对青藏高原气候平均降水的模拟有明显改进, 包括降水年循环以及夏季降水的空间分布等。分辨率为180 km、120 km、60 km、20 km的MRI模式模拟的青藏高原7月平均降水绝对误差分别为2.2 mm/d、1.2 mm/d、0.7 mm/d、0.2 mm/d。另外, 高分辨率模式模拟的青藏高原夏季水汽输送通量的年际变化也更接近观测。当分辨率达到20 km时, MRI模式模拟的西风水汽输送指数与观测的相关系数达到0.43, 通过了0.1显著性水平的显著性检验。但MRI模式对青藏高原夏季降水的年际变化以及气候平均水汽输送通量的模拟技巧并不随分辨率的增加有明显提高。低分辨率模式中模拟降水量偏大、印度季风槽偏强的现象在高分辨率模式中仍然存在。     

CAM3模式海气湍流通量参数化的改进及其应用

通过对流性阵风参数化方法,在CAM3原有海气湍流通量参数化方案(CAM3方案)中引入边界层自由对流和降水深对流对海表湍流通量的贡献,改进了CAM3模式的海气湍流通量参数化方案(CAM3 ME方案).在此基础上,利用观测海温积分改进的CAM3模式,分析改进模式对冬(DJF)、夏季(JJA)大气环流异常的模拟性能.结果表明,采用改进的海气湍流通量参数化方案,模式对冬(DJF)、夏季(JJA)大气环流异常年际变化的模拟能力有了很大提高,尤其是冬季(DJF)北太平洋和北美大陆地区以及夏季(JJA)南半球海洋上空.     

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。     

Development and validation of a regional coupled atmosphere lake model for the Caspian Sea Basin

We present a validation analysis of a regional climate model coupled to a distributed one dimensional (1D) lake model for the Caspian Sea Basin. Two model grid spacings are tested, 50 and 20 km, the simulation period is 1989–2008 and the lateral boundary conditions are from the ERA-Interim reanalysis of observations. The model is validated against atmospheric as well as lake variables. The model performance in reproducing precipitation and temperature mean seasonal climatology, seasonal cycles and interannual variability is generally good, with the model results being mostly within the observational uncertainty range. The model appears to overestimate cloudiness and underestimate surface radiation, although a large observational uncertainty is found in these variables. The 1D distributed lake model (run at each grid point of the lake area) reproduces the observed lake-average sea surface temperature (SST), although differences compared to observations are found in the spatial structure of the SST, most likely as a result of the absence of 3 dimensional lake water circulations. The evolution of lake ice cover and near surface wind over the lake area is also reproduced by the model reasonably well. Improvements resulting from the increase of resolution from 50 to 20 km are most significant in the lake model. Overall the performance of the coupled regional climate—1D lake model system appears to be of sufficient quality for application to climate change scenario simulations over the Caspian Sea Basin.     

Interannual variability and regional climate simulations

Summary An assessment is made of a regional climate model's skill in simulating the mean climatology and the interannual variability experienced in a specific region. To this end two ensembles comprising three realizations of month-long January and July simulations are undertaken with a limited are a operational NWP model. The modelling suite is driven at its lateral boundaries by analysed meteorological fields and the computational domain covers Europe and the North-western Atlantic with a horizontal resolution of 56 km.Validation is performed against both operational ECMWF analyses and objectively analysed precipitation fields from a network of ~ 1400 SYNOP rain gauge stations. Analysis of the simulated ensemble-mean climatology indicates that the model successfully reproduces both the winter and summer distributions of the primary dynamical and thermodynamical field, and also provides a reasonable representation of the measured precipitation over most of Europe. Typically the domain averaged model-biases are below 0.5 K for temperature and 0.1 g/kg for specific humidity. Analysis of the interannual variability reveals that the model captures the wintertime changes including that of the precipitation distribution, but in contrast the summertime precipitation totals for the individual years is not simulated satisfactorily and only partially reproduces the observed regional interannual variability.The latter shortcomings are related to the following factors. Firstly the model bias in the dynamical fields is somewhat larger for summer than winter, while at the same time summertime interannual variability is associated with weaker effects in the dynamical fields. Secondly the summertime precipitation distribution is more substantially affected by small-scale moist convection and surface hydrological processes. Together these two factors suggest that summertime precipitation over continental extratropical land masses might be intrinsically less predictable than wintertime synoptic scale precipitation.With 17 Figures     

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.     

土壤湿度年际变化对中国区域极端气候事件模拟的影响研究 I. 基于CAM3.1的模式评估

利用NCAR大气模式CAM3.1对中国区域近40年的极端气候事件进行了模拟试验;在此基础上, 利用1961～2000年中国区域452站的逐日最高、最低气温和降水资料, 从气候平均、年际变化和长期变化趋势等方面全面评估了该模式对中国极端气候事件的模拟能力。结果表明:(1)模式对中国区域极端气候指数气候平均态的大尺度空间分布特征具有一定的模拟能力;模式对极端降水指标空间分布的模拟能力较好, 而对极端气温指标的模拟较差;模式对极端气候指标的模拟存在系统性的偏差, 模拟的极端降水的系统性偏差要远大于对极端温度的模拟。(2)模式对极端气温指数的年际变化特征具有较强的模拟能力, 而对极端降水指数的年际变化基本没有模拟能力;模式模拟的各极端降水指标的年际变幅与观测存在较大的偏差。(3)模式较好地模拟出了暖夜和暖昼指数在中国大部分区域的增加趋势, 但变幅较实测偏小;模式对热浪持续指数长期趋势的模拟则相对略差。模式对极端气温指标长期趋势的模拟能力总体优于对极端降水指标的模拟。模式对极端降水频次和中雨日数长期趋势的模拟尚可, 但对持续湿期长期趋势的空间分布模拟较差。研究结果可为该模式用于极端气候的模拟研究提供一定参考。     

Evaluation of an ensemble of regional climate model simulations over South America driven by the ERA-Interim reanalysis: model performance and uncertainties

The capability of a set of 7 coordinated regional climate model simulations performed in the framework of the CLARIS-LPB Project in reproducing the mean climate conditions over the South American continent has been evaluated. The model simulations were forced by the ERA-Interim reanalysis dataset for the period 1990–2008 on a grid resolution of 50 km, following the CORDEX protocol. The analysis was focused on evaluating the reliability of simulating mean precipitation and surface air temperature, which are the variables most commonly used for impact studies. Both the common features and the differences among individual models have been evaluated and compared against several observational datasets. In this study the ensemble bias and the degree of agreement among individual models have been quantified. The evaluation was focused on the seasonal means, the area-averaged annual cycles and the frequency distributions of monthly means over target sub-regions. Results show that the Regional Climate Model ensemble reproduces adequately well these features, with biases mostly within ±2 °C and ±20 % for temperature and precipitation, respectively. However, the multi-model ensemble depicts larger biases and larger uncertainty (as defined by the standard deviation of the models) over tropical regions compared with subtropical regions. Though some systematic biases were detected particularly over the La Plata Basin region, such as underestimation of rainfall during winter months and overestimation of temperature during summer months, every model shares a similar behavior and, consequently, the uncertainty in simulating current climate conditions is low. Every model is able to capture the variety in the shape of the frequency distribution for both temperature and precipitation along the South American continent. Differences among individual models and observations revealed the nature of individual model biases, showing either a shift in the distribution or an overestimation or underestimation of the range of variability.     

MRI模式对华南春雨气候态及年际变率的模拟：不同模式分辨率的比较

本文利用日本气象研究所（MRI）参加第五次国际耦合模式比较计划（CMIP5）的大气环流模式在高、中、低三种分辨率下的AMIP试验结果,评估了其对华南春雨气候态和年际变率的模拟能力,比较了不同分辨率的模拟结果。结果表明,三种不同水平分辨率（120 km、60 km和20 km）的模式均能再现北半球春季位于中国东南部的降水中心。相较于120 km模式,20 km模式能够更为合理地模拟出华南春雨位于南岭—武夷山脉的降水中心。水汽收支分析表明,60 km、20 km模式高估了水汽辐合,使得华南春雨的降水强度被高估。在年际变率方面,在三种分辨率下,模式均能较好地再现观测中El Ni?o衰减年春季的西北太平洋反气旋以及华南春雨降水正异常。较之120 km模式,60 km、20 km模式模拟的降水正异常的空间分布和强度更接近观测,原因是后者模拟的El Ni?o衰减年春季华南地区的水平水汽平流异常更接近观测。本研究表明,发展高分辨率气候模式是提高华南春雨的气候态和年际变率模拟水平的有效途径之一。     

Validation and sensitivity of the global hydrologic budget in stand-alone simulations with the ISBA land-surface scheme

 Global soil moisture data of high quality and resolution are not available by direct observation, but are useful as boundary and initial conditions in comprehensive climate models. In the framework of the GSWP (Global Soil Wetness Project), the ISBA land-surface scheme of Météo-France has been forced with meteorological observations and analyses in order to study the feasibility of producing a global soil wetness climatology at a 1°×1° horizontal resolution. A control experiment has been performed from January 1987 to December 1988, using the ISLSCP Initiative I boundary conditions. The annual mean, the standard deviation and the normalised annual harmonic of the hydrologic fields have been computed from the 1987 monthly results. The global maps which are presented summarise the surface hydrologic budget and its annual cycle. The soil wetness index and snow cover distributions have been compared respectively to the results of the ECMWF reanalysis and to satellite and in situ observations. The simulated runoff has been validated against a river flow climatology, suggesting a possible underestimation over some large river basins. Besides the control run, other simulations have been performed in order to study the sensitivity of the hydrologic budget to changes in the surface parameters, the precipitation forcing and the runoff scheme. Such modifications have a significant impact on the partition of total precipitation into evaporation and runoff. The sensitivity of the results suggests that soil moisture remains one of the most difficult climatological parameters to model and that any computed soil wetness climatology must be considered with great caution. Received: 3 January 1997 / Accepted: 19 August 1987     

Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.     

Seasonal climatology of cut-off lows and associated precipitation patterns over Northeast China

Cut-off lows (COLs) are significantly associated with many convective events and anomalous regional climate in the Northeast China. By using 49-year NCEP/NCAR reanalysis data, COL events are detected and tracked by an objective and automatic method based on synoptic concept model. Based on this dataset and daily rain-gauge records in Northeast China during 1979–2005, seasonal climatology of COLs and associated precipitation patterns over Northeast China are investigated. Most COLs have a short lifetime of less than a week and have a spatial size ranging from 500 to 1,000 km, with slight seasonal differences. Temporal variation of COL occurrence exhibits a seasonal cycle, with a peak in summer, and considerable interannual variability. The COLs tend to occur more frequently over the northern Northeast China Plain, and the center for maximum frequency shows a zonal oscillation, with an extension to continent in summer and a shift to western North Pacific coast in winter. Most COLs form to the east of Lake Baikal and decay over the western North Pacific coast. COLs are apt to move along east or southeast passages around the year, and tracks are relatively more complicated in warm seasons. About a quarter of annual mean precipitation over Northeast China is associated with COLs. Moreover, COL-associated precipitation contributes greatly to total precipitation in northern and northwestern parts of Northeast China, and the ratios of COL contribution are stronger during spring and autumn than in summer.     

Surface energy, water and carbon cycle in China simulated by the Australian community land surface model (CABLE)

Through an Australia-China climate change bilateral project, we analyzed results of 51-year global offline simulations over China using the Australian community atmosphere biosphere land exchange (CABLE) model, focusing on integrated studies of its surface energy, water and carbon cycle at seasonal, interannual and longer time-scales. In addition to the similar features in surface climatology between the CABLE simulation and those derived from the global land-surface data assimilation system, comparison of surface fluxes at a CEOP reference site in northeast China also suggested that the seasonal cycles of surface evaporation and CO₂ flux are reasonably simulated by the model. We further assessed temporal variations of model soil moisture with the observed variations at a number of locations in China. Observations show a soil moisture recharge–discharge mechanism on a seasonal time scale in central-east China, with soil moisture being recharged during its summer wet season, retained in its winter due to low evaporation demand, and depleted during early spring when the land warms up. Such a seasonal cycle is shown at both 50- and 100-cm soil depths in observations while the model only shows a similar feature in its lower soil layers with its upper layer soil moisture varying tightly with rainfall seasonal cycle. In the analysis of the model carbon cycle, the net primary productivity (NPP) has similar spatial patterns as the ones derived from an ecosystem model with remote sensing. The simulated interannual variations of NPP by CABLE are consistent with the results derived from remote sensing-based and process-based studies over the period of 1981–2000. Nevertheless an upward trend from observations is not presented in the model results. The model shows a downward trend primarily due to the constant CO₂ concentration used in the experiment and a large increase of autotrophic respiration caused by an upward trend in surface temperature forcing data. Furthermore, we have compared river discharge data from the model experiments with observations in the Yangtze and Yellow River basins in China. In the Yangtze River basin, while the observed interannual variability is reasonably captured, the model significantly underestimates its river discharge, which is consist with its overestimation of evaporation in the region. In the Yellow River basin, the magnitudes of the river discharge is similar between modeled and observed but its variations are less skillfully captured as seen in the Yangtze River region.     

东亚中高纬土壤温度资料评估与分析

本文以一套俄罗斯土壤温度历史观测资料RHSTD为基础,分析了四套土壤温度产品[ERA-Interim再分析资料、两套陆面模式离线运行产品ERA-Interim/Land（简称ERA-Land）和MERRA-Land、以及一套二十世纪再分析资料NOAA-CIRES 20CR]在东亚中高纬的可靠性,并重点关注春夏季,主要结论如下:观测地温在0~2 m波动较大,随季节在0℃上下摆动,而2 m以下地温稳定少变,并且在60°N以北地区出现永久冻结。四套地温产品较好地反映了这些特征。无论春夏,还是年平均,四套地温产品气候态都呈“南暖北冷”的特征,但ERA-Land的空间分布与观测最接近。就季节循环而言,ERA-Land最能反映该地区土壤的冻融过程和土壤温度的季节演变。四套地温产品年际变率（标准差）与观测的差异随季节和土壤层变化大,情况比较复杂。就年际变化趋势而言,四套地温产品与观测的相关性,夏季好于春季,表层好于深层,并且ERA-Land土壤温度拥有四套地温产品最多的共性,最能反映观测地温的年际变化。