LASG耦合气候系统模式FGCM-1.0

本文描述了中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)最新发展的一个耦合气候系统模式的基本性能. 该模式是在LASG灵活的全球耦合气候系统模式（英文缩写为FGCM）的初始版本FGCM-0的基础上发展而来的,是该系列耦合模式的第二个版本,即FGCM-1.0. FGCM-1.0通过一个通量耦合器将大气、海洋和海冰三个分量模式耦合在一起,其中海洋分量模式是LASG发展的一个涡相容分辨率（eddy-permitting）全球海洋环流模式,大气和海冰分量模式则为美国国家大气研究中心（NCAR）的大气环流模式CAM2和海冰模式CSIM4. 耦合模式完整地考虑了海气界面上的动量、热量和淡水通量交换,尽管在模式中没有使用任何形式的人为的通量调整或者通量距平方案,模式还是比较合理地模拟出基本的气候形态. 通过对该耦合模式长期积分结果的进一步分析发现,模式能够比较好地模拟出厄尔尼诺－南方涛动（ENSO）以及印度洋偶极子事件的基本特征;与FGCM系列耦合模式的最初版本FGCM-0相比,FGCM-1.0模拟的北赤道逆流（NECC）和ENSO循环更加真实.     

Sensitivity of sea ice and ocean simulations to sea ice salinity in a coupled global climate model

The impacts of the spatiotemporal variations of sea ice salinity on sea ice and ocean characteristics have not been studied in detail, as the existing climate models neglect or misrepresent this process. To address this issue, this paper formulated a parameterization with more realistic sea ice salinity budget, and examined the sensitivity of sea ice and ocean simulations to the ice salinity variations and associated salt flux into the ocean using a coupled global climate model. Results show that the inclus...     

用全球大气环流模式嵌套区域气候模式模拟东亚现代气候

将区域气候模式RegCM2与中国科学院大气物理研究所的9层全球格点大气环流模式IAP-AGCM单向嵌套,对东亚现代气候进行数值模拟研究,同时检验和分析该嵌套模式的性能.已完成的10年积分结果表明,单向嵌套RegCM2由于具有较高分辨率和较完善的物理过程,因此对地面气温和降水的空间分布形势和季节变化趋势都有较好的模拟能力,且较与之嵌套的IAP-AGCM的模拟效果有较大改善,如在中国区域,它模拟的年均地面气温与实况的空间相关系数由全球环流模式的0.92提高到0.94,模拟的年均降水由0.5提高到0.7. 这与嵌套RegCM2能模拟出IAP-AGCM所不能分辨的中尺度信号有很大关系.     

Impact of anticipated climate change on direct groundwater recharge in a humid tropical basin based on a simple conceptual model

A simple conceptual semi‐distributed modelling approach for assessing the impacts of climate change on direct groundwater recharge in a humid tropical river basin is investigated. The study area is the Chaliyar river basin in the state of Kerala, India. Many factors affecting future groundwater recharge include decrease or increase in precipitation and temperature regimes, coastal flooding, urbanization and changes in land use. The model is based on the water‐balance concept and links the atmospheric and hydrogeologic parameters to different hydrologic processes. It estimates daily water‐table fluctuation and is calibrated and validated using 10 years of data. Data for the first 6 years (2000 to 2005) is used for model calibration, and data for the remaining four years (2006 to 2009) is used for validation. For assessing the impact of predicted climate change on groundwater recharge during the period 2071–2100, temperature and precipitation data in two post climate change scenarios, A2 and B2, were predicted using the Regional Climate Model (RCM), PRECIS (Providing Regional Climates for Impact Studies). These data were then corrected for biases and used in a hydrologic model to predict groundwater recharge in the post climate change scenario. Due to lack of reliable data and proper knowledge as to the magnitude and extent of future climatic changes, it may not be possible to include all the possible effects quantitatively in groundwater recharge modelling. However, the study presents a scientific method to assess the impact of predicted climate change on groundwater recharge and would help engineers, hydrologists, administrators and planners to devise strategies for the efficient use as well as conservation of freshwater resources. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulations of LGM climate of East Asia by regional climate model

ClimateconditionsintheLastGlacialMaximum(LGM)wereremarkablydifferentfromthepresentones.LGMglobalmeantemperaturewas5℃-10℃dropbutprecipitationdecreasescommonly.LGMhasbecomethekeyphasetoreconstructtheearthenvironmentalfield,retrieveextremecoldclimatecondit…     

Land use effects on climate in China as simulated by a regional climate model

A regional climate model (RegCM3) nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987―2001), one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic ac- tivities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter, land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change signifi- cantly affects summer climate in southern China, yielding increased precipitation over the region, de- creased temperature along the Yangtze River and increased temperature in the South China area (south-end of China). In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.     

Improvement of snowpack simulations in a regional climate model

To improve simulations of regional‐scale snow processes and related cold‐season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth‐generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land‐surface model. One important cause for the underestimated SWE in Noah is its unrealistic land‐surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow‐season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near‐surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over‐predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5–CLM3 due to the lower evaporation resulting from the longer snow duration. Copyright © 2011 John Wiley & Sons, Ltd.     

Weather and seasonal climate prediction for flood planning in the Yangtze River Basin

This paper describes the use of numerical weather and climate models for predicting severe rainfall anomalies over the Yangtze River Basin (YRB) from several days to several months in advance. Such predictions are extremely valuable, allowing time for proactive flood protection measures to be taken. Specifically, the dynamical climate prediction system (IAP DCP-II), developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP), is applied to YRB rainfall prediction and flood planning. IAP DCP-II employs ensemble prediction with dynamically conditioned perturbations to reduce the uncertainty associated with seasonal climate prediction. IAP DCP-II was shown to successfully predict seasonal YRB summer flooding events based on a 15-year (1980–1994) hindcast experiment and the real-time prediction of two summer flooding events (1999 and 2001). Finally, challenges and opportunities for applying seasonal dynamical forecasting to flood management problems in the YRB are discussed.     

Sensitivity of the central Asian climate to uplift of the Tibetan Plateau in the coupled climate model (MRI-CGCM1)

Abstract   The relationship between the altitude of the Tibetan Plateau and climate change in central Asia was investigated through a numeric experiment using the Meteorological Research Institute (MRI) coupled atmosphere–ocean general circulation model I (MRI-CGCM1). The results suggest that summer precipitation in central Asia decreased significantly as the Tibetan Plateau rose in height. Spring precipitation, however, increased during initial growth stages when the plateau height was up to 40% of its present-day height, and then decreased with further plateau growth. During the Tibetan Plateau uplift, the difference between precipitation and evaporation was minimal during spring. When the plateau attained a height exceeding 60% of its present height, relatively low precipitation but high evaporation in spring led to a lower amount of ground moisture. In the case of the high plateau, sensible heat flux during summer and fall largely exceeded latent heat flux. Change was particularly significant for cases when the plateau reached 40–60% of its present-day height. The duration of the predominant sensible heat flux became longer with the uplift of the Tibetan Plateau. The period in which latent heat exceeded sensible heat seems to have been restricted to winter and early spring. The numeric experiments suggest that a significant drying of central Asia corresponded to the period in which the Tibetan Plateau exceeded approximately half its present-day height.     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Reconstruction of Conceptual Prediction Model for the Three Rainfall Patterns in the summer of eastern China under global warming

With the influence of global warming,the global climate has undergone significant inter-decadal variation since the late 1970s.Although El Nio-Southern Oscillation(ENSO)has been the strongest signal for predicting global climate inter-annual variability,its relation with the summer rainfall in China has significantly changed,and its indicative function on the summer rainfall in China has weakened.This has led to a significant decrease in the accuracy rate of early conceptual prediction models for the Three Rainfall Patterns in the summer of eastern China.On the basis of the difference analysis of atmospheric circulation system configuration in summer,as well as the interaction of ocean and atmospheric in previous winter between two phases,i.e.before and after the significant global warming(1951 to 1978 and 1979 to 2012,respectively),we concluded that(1)Under different inter-decadal backgrounds,the atmospheric circulations that impacted the Three Rainfall Patterns in the summer of eastern China showed consistency,but in the latter phase of the global warming,the Western Pacific Subtropical High(WPSH)was on the strong side,the position of which was in the south,and the blocking high in the Eurasia mid-high latitudes was active,while the polar vortex extended to the south,and meridional circulation intensified.This circulation background may have been conducive to the increase of the circulation frequency of Patterns II and III,and the decrease of the circulation frequency of Pattern I,thus leading to more Patterns II and III and fewer Pattern I in the summer rainfall of eastern China.(2)In the former phase,the corresponding previous winter SST fields of different rainfall patterns showed visible differences.The impact of ENSO on North Pacific Oscillation(NPO)was great,and the identification ability of which on Patterns I and II of summer rainfall was effective.In the latter phase,this identification ability decreased,while the impact of ENSO on the Pacific/North American(PNA)teleconnection pattern increased,and the identification ability of the PNA on Patterns II and III also increased.Based on the new inter-decadal climate background,this study reconstructs the conceptual prediction model for the Three Rainfall Patterns in summer of eastern China by using the previous winter PNA and the Eurasian(EU)teleconnection indexes.The fitting effect was satisfying,though it is necessary to be further tested.     

Application of a time-magnitude prediction model for earthquakes

In this paper we discuss the physical meaning of the magnitude-time model parameters for earthquake prediction. The gestation process for strong earthquake in all eleven seismic zones in China can be described by the magnitude-time prediction model using the computations of the parameters of the model. The average model parameter values for China are： b = 0.383, c=0.154, d = 0.035, B = 0.844, C = -0.209, and D = 0.188. The robustness of the model parameters is estimated from the variation in the minimum magnitude of the transformed data, the spatial extent, and the temporal period. Analysis of the spatial and temporal suitability of the model indicates that the computation unit size should be at least 4°× 4°for seismic zones in North China, at least 3° × 3° in Southwest and Northwest China, and the time period should be as long as possible.     

地震预报中震级-时间模型的应用

本文从震级-时间模型的表达式出发,讨论了模型参数所含的物理意义,通过计算中国大陆各地震带的震级-时间模型参数,认为只有其中11条地震带的强震孕震过程可以用该模型来表达,其平均参数为b=0.383,c=0.154,d=0.035,B=0.844,C=-0.209,D=0.188。通过变换资料的震级下限、时间域和空间域的计算结果,讨论了模型参数的鲁棒性。通过对模型应用空间范围的分析,在华北地震区,在利用震级—时间模型对未来的地震危险进行预测时,计算单元应不小于4°×4°,而在西北和西南地区,计算单元不要小于3°×3°。而通过对模型应用时间范围的分析,在应用模型进行预测时,资料时间域要尽量长一些。     

基于Sugeno型模糊推理的震中烈度预测模型

以Sugeno型模糊推理系统为基础,建立了以震级和震源深度为输入,以震中烈度为输出的震中烈度预测模型,并以四川地区震例数据为例,对模型构建的关键环节进行了详细的说明.通过与参考文献中的拟合模型进行预测数据对比分析,可得本文的推理预测模型精度更高,误差更小,且有更强的扩展性.     

基于变形P-L模型的矩阵方程迭代精细横波预测

横波速度预测问题的关键有两个,一是如何建立合理的岩石物理模型,二是针对建立的横波预测目标函数,如何准确高效地求解.针对第一个问题,对Pride模型和Lee模型(P-L模型)进行变形,提出拟固结指数的概念,将干岩石模量和岩石基质模量相联系,变形后的P-L模型在没有降低P-L模型准确度的情况下简化了问题的复杂度,建立起了饱和流体岩石弹性模量与干岩石模量、岩石基质模量、混合流体模量之间的关系,进而计算理论上的纵波速度,并通过比较实测纵波速度与计算的理论纵波速度大小,最终建立了横波预测的目标函数.针对第二个问题,借鉴了地震反演的思路,将该目标函数的最优化问题转化为线性矩阵方程组迭代求解问题,通过几步迭代就可以求解出合适的拟固结指数,进而得到预测横波速度.实际验证和应用表明,该横波预测方法具有很好的稳定性和准确性,并且岩石物理模型的构建和目标函数的求解思路可用于其他储集类型地层的横波预测.     

基于GIS技术的钢筋混凝土框架结构震害预测系统设计

根据传统的钢筋混凝土框架结构震害预测方法，利用地理信息系统软件ArcView，研制了一套钢筋混凝土框架结构震害预测与评价系统。这一预测系统不仅适用于钢筋混凝土框架结构，而且适用于底层框架和内框架结构。     

Continuous prediction of clay‐bed stream erosion in response to climate model output for a small urban watershed

The response of the semi‐alluvial clay‐bed Watts Creek is assessed subject to climate change. Climate impacts are expected to have regional variability, and few studies have assessed the impacts of future climate in a small urban watershed. The 21‐km² watershed located in Ottawa, Ontario, Canada, is highly urbanized (68%) and agricultural (20%) with limited forest cover (12%). Continuous simulations were performed using the SWMHYMO lumped hydrologic modelling platform for the open water year, excluding spring freshet (April 1 to October 31). A shear stress exceedance and stream power erosion routine was added to the platform to calculate erosion potential. To account for uncertainty in the collected data, 9 different field datasets were used to calibrate the model, each leading to a distinct set of calibrated parameter values. The difference between the datasets lies in the choice of the rating curves and calibration period. The 2041–2080 precipitation outputs of the 4th version of the Canadian Regional Climate Model (CanRCM4) ran under representative concentration pathways (RCPs) 4.5 and 8.5 at the MacDonald Cartier International Airport were downscaled using quantile matching and then used as input to the continuous hydrologic model. For each set of calibrated parameters, a cumulative effective work index based on the reach‐averaged shear stress was calculated for Watts Creek using both the historic (1967–2007) and projected future (2041–2080) flows, using a bed material critical shear stress for entrainment of 3.7 Pa. These results suggest an increase of 75% (respectively 139%) under RCP4.5 (respectively RCP8.5) in cumulative effective work index compared with historic conditions for the average measured bed strength. The work index increase is driven by an increased occurrence of above‐threshold events and, more importantly, by the increased frequency of large events. The predicted flow regime under climate change would significantly alter the erosion potential and stability of Watts Creek.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Hydrologic impact of regional climate change for the snow‐fed and glacier‐fed river basins in the Republic of Tajikistan: statistical downscaling of global climate model projections

Climate change due to global warming is a public concern in Central Asia. Because of specific orography and climate conditions, the republic of Tajikistan is considered as the main glacial center of Central Asia. In this study, regional climate change impacts in the two large basins of Tajikistan, Pyanj and Vaksh River basins located in the upstream sector of the Amu Darya River basin are analysed. A statistical regression method with model output statistics corrections using the ground observation data, Willmott archived dataset and GSMaP satellite driven dataset, was developed and applied to the basins to downscale the Global Climate Model Projections at a 0.1‐degree grid and to assess the regional climate change impacts at subbasin scale. It was found that snow and glacier melting are of fundamental importance for the state of the future water resources and flooding at the target basins since the air temperature had a clearly increasing trend toward the future. It was also found that the snowfall will decrease, but the rainfall will increase because of the gradual increase in the air temperature. Such changes may result in an increase in flash floods during the winter and the early spring, and in significant changes in the hydrological regime during a year in the future. Furthermore, the risks of floods in the target basins may be slightly increasing because of the increase in the frequencies and magnitudes of high daily precipitation and the increase in the rapid snowmelt with high air temperatures toward the future. Copyright © 2012 John Wiley & Sons, Ltd.