区域海气耦合模式FROALS的发展及其应用

区域海气耦合模式是研究局地海气相互作用过程影响气候变率的重要平台,也是对全球气候模式进行"动力降尺度"的重要工具.本文介绍了LASG(State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics)/IAP(Institute of Atmospheric Physics)发展的区域海气耦合模式FROALS(Flexible Regional Ocean-Atmosphere-Land System model),并总结了过去五年围绕该区域海气耦合模式开展的研究工 作.FROALS的特点之一是有两个完全不同的大气模式分量和海洋模式分量选项,可以适应不同的模拟研究需 求.针对区域海气耦合模式在西北太平洋地区的模拟偏差,通过分步骤考察不同大气模式分量和不同海洋模式分量对模式模拟性能的影响,指出大气模式是导致区域海气耦合偏差的主要分量.通过改进对流触发的相对湿度阈值标准,有效地改善了此前区域海气耦合模式在亚洲季风区普遍出现的"模拟海温冷偏差".改进的FROALS对西北太平洋地区的大气和海洋环境有较好的模拟能力,合理地再现了西北太平洋地区表层洋流气候态和年际变率.较之非耦合模式,考虑区域海气耦合过程后,改进了东亚和南亚地区的降水和热带气旋潜势年际变率的模拟.最后,针对东亚—西北太平洋地区,利用FROALS对IAP/LASG全球气候模式模拟和预估的结果进行了动力降尺 度,得到了东亚区域50 km高分辨率区域气候变化信息.分析显示,FROALS模拟得到的东亚区域气候较之全球气候模式和非耦合区域气候模式结果具有明显的"增值",显示出区域海气耦合模式在该区域良好的应用前景.     

Evaluation of ocean data assimilation in CAS-ESM-C: Constraining the SST field

A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model(CASESM-C) through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic fields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of output from the system, the climatology and interannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, but it still suffers from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Ni ?no evolution, is basically reproduced by the system. The system can also simulate the observed SST–rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.     

Performance of RegCM4 over Major River Basins in China

A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.     

Relevance of soil moisture for seasonal climate predictions: a preliminary study

In the framework of the Global Soil Wetness Project (GSWP), the ISBA land-surface scheme of the ARPEGE atmospheric general circulation model has been forced with meteorological observations and analyses in order to produce a two-year (1987–1988) soil moisture climatology at a 1^°×1^° horizontal resolution. This climatology is model dependent, but it is the climatology that the ARPEGE model would produce if its precipitation and radiative fluxes were perfectly simulated. In the present study, ensembles of seasonal simulations (March to September) have been performed for 1987 and 1988, in which the total soil water content simulated by ARPEGE is relaxed towards the GSWP climatology. The results indicate that the relaxation has a positive impact on both the model's climatology and the simulated interannual variability, thereby confirming the utility of the GSWP soil moisture data for prescribing initial or boundary conditions in comprehensive climate and numerical weather prediction models. They also demonstrate the relevance of soil moisture for achieving realistic simulations of the Northern Hemisphere summer climate. In order to get closer to the framework of seasonal predictions, additional experiments have been performed in which GSWP is only used for initialising soil moisture at the beginning of the summer season (the relaxation towards GSWP is removed on 1st June). The results show a limited improvement of the interannual variability, compared to the simulations initialised from the ARPEGE climatology. However, some regional patterns of the precipitation differences between 1987 and 1988 are better captured, suggesting that seasonal predictions can benefit from a better initialisation of soil moisture.     

西北太平洋热带气旋气候变化的若干研究进展

热带气旋气候变化研究不仅是当前国际热带气旋气候界的热点科学问题,而且也是具有现实意义的社会问题,各国气象学者和科学家们对此进行了广泛的研究。虽然热带气旋活动与气候变化之间的关系及其相应的内在物理机制至今还处在探究之中,但是近20多年来热带气旋气候学的研究还是取得了显著的进展。本文主要针对濒临中国的西北太平洋海域,回顾了热带气旋活动季节内、年际、年代际变化及其全球变暖背景下的变化趋势的气候学研究。此外,文中也对西北太平洋热带气旋气候学的研究进行了展望,并提出了该领域中一些亟待解决的科学问题。     

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941     

一个灵活的海洋——大气耦合环流模式

Based on the National Center for Atmospheric Research (NCAR) Climate System Model version 1(CSM-1), a Flexible coupled General Circulation Model version 0 (FGCM-0) is developed in this study through replacing CSM-1＇s oceanic component model with IAP L30T63 global oceanic general circulation model and some necessary modifications of the other component models. After the coupled model FGCM--0 is spun up for dozens of years, it has been run for 60 years without flux correction. The model does not only show the reasonable long-term mean climatology, but also reproduce a lot of features of the interannual variability of climate, e.g. the ENSO-like events in the tropical Pacific Ocean and the dipole mode pattern in the tropical Indian Ocean. Comparing FGCM-0 with the NCAR CSM-1, some common features are found, e.g. the overestimation of sea ice in the North Pacific and the simulated double ITCZ etc.The further analyses suggest that they may be attributed to errors in the atmospheric model.     

Monitoring sea level changes

Future sea level rise arouses concern because of potentially deleterious impacts to coastal regions. These will stem not only from the loss of land through inundation and erosion, but also from increased frequency of storm floods, with a rising base level, even with no change in storm climatology, and from saltwater intrusion and greater amounts of waterlogging. Current sea level trends are important in formulating an accurate baseline for future projections. Sea level, furthermore, is an important parameter which integrates a number of oceanic and atmospheric processes. The ocean surface demonstrates considerable variability on diurnal, seasonal, and interannual time scales, induced by winds, storm waves, coastal upwelling, and geostrophic currents. Secular trends in sea level arise from changes in global mean temperature and also from crustal deformation on local to regional scales. The challenge facing researchers is how best to extract the climate signal from this noise.This paper re-examines recent estimates of sea level rise, discusses causes of variability in the sea level records, and describes methods employed to filter out some of these contaminating signals. Evidence for trends in long-term sea level records and in extreme events is investigated. Application of satellite geodesy to sea level research is briefly reviewed.     

Very high-resolution climate simulation over Fiji using a global variable-resolution model

A high-resolution climate model simulation has been performed for the first time for Fiji’s climatology. The simulation involved a numerical experiment for a 10-year period (1975–1984), and was conducted at a horizontal resolution of 8 km in a stretched-grid configuration, which is currently the highest resolution at which a global climate model has been applied for regional climatological simulations. Analysis of model-generated data demonstrates a fairly good skill of the CSIRO Conformal-Cubic Atmospheric Model (C-CAM) in the simulation of the annual cycles of maximum and minimum temperatures and rainfall at selected locations in Fiji. The model has also successfully reproduced the pattern of maximum and minimum surface air temperatures between the western and central divisions of Fiji. Model simulation of spatial and temporal distribution of monthly total rainfall (10-year mean) over the main island of Viti Levu in Fiji shows that it reproduces the observed intraseasonal and interannual variability; the influence of the El Niño phenomena has also been captured well in the model-simulated rainfall.     

An assessment of oceanic variability for 1960–2010 from the GFDL ensemble coupled data assimilation

The Geophysical Fluid Dynamics Laboratory has developed an ensemble coupled data assimilation (ECDA) system based on the fully coupled climate model, CM2.1, in order to provide reanalyzed coupled initial conditions that are balanced with the climate prediction model. Here, we conduct a comprehensive assessment for the oceanic variability from the latest version of the ECDA analyzed for 51 years, 1960–2010. Meridional oceanic heat transport, net ocean surface heat flux, wind stress, sea surface height, top 300 m heat content, tropical temperature, salinity and currents are compared with various in situ observations and reanalyses by employing similar configurations with the assessment of the NCEP’s climate forecast system reanalysis (Xue et al. in Clim Dyn 37(11):2511–2539, 2011). Results show that the ECDA agrees well with observations in both climatology and variability for 51 years. For the simulation of the Tropical Atlantic Ocean and global salinity variability, the ECDA shows a good performance compared to existing reanalyses. The ECDA also shows no significant drift in the deep ocean temperature and salinity. While systematic model biases are mostly corrected with the coupled data assimilation, some biases (e.g., strong trade winds, weak westerly winds and warm SST in the southern oceans, subsurface temperature and salinity biases along the equatorial western Pacific boundary, overestimating the mixed layer depth around the subpolar Atlantic and high-latitude southern oceans in the winter seasons) are not completely eliminated. Mean biases such as strong South Equatorial Current, weak Equatorial Under Current, and weak Atlantic overturning transport are generated during the assimilation procedure, but their variabilities are well simulated. In terms of climate variability, the ECDA provides good simulations of the dominant oceanic signals associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation, and Atlantic Meridional Overturning Circulation during the whole analyzed period, 1960–2010.     

Impacts of ocean gateway and basin width on Tertiary tropical climate variability in a prototype model

Using a simple tropical climate model, we investigated possible impacts of changes in oceanic seaways (Panama and Tethys) and ocean basin sizes (great Pacific and narrow Atlantic) on tropical climate variability during Tertiary. Our model showed that the opening of seaways had little influence on climate variability in the tropical Pacific because the climate variability in the Pacific Ocean’s large basins were internally generated, regardless of the variation in the tropical Atlantic Ocean. Conversely, the climate variability in the tropical Atlantic Ocean was highly dependent on the tropical Pacific Ocean; thus, an opening seaway, particularly the Panama seaway, was crucial in generating the interannual variability in the tropical Atlantic Ocean. We also found that in the Pacific Ocean, basin size strongly modified the period and amplitude of the interannual variability of both the Pacific and Atlantic Oceans due to ocean wave dynamics.     

Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model

The COSMO-CLM (CCLM) model is applied to perform regional climate simulation over the second phase of CORDEX-East Asia (CORDEX-EA-II) domain in this study. Driven by the ERAInterim reanalysis data, the model was integrated from 1988 to 2010 with a high resolution of 0.22°. The model’s ability to reproduce mean climatology and climatic extremes is evaluated based on various aspects. The CCLM model is capable of capturing the basic features of the East Asia climate, including the seasonal mean patterns, interannual variations, annual cycles and climate extreme indices for both surface air temperature and precipitation. Some biases are evident in certain areas and seasons. Warm and wet biases appear in the arid and semi-arid areas over the northwestern and northern parts of the domain. The simulated climate over the Tibetan Plateau is colder and wetter than the observations, while South China, East China, and India are drier. The model biases may be caused by the simulated anticyclonic and cyclonic biases in low-level circulations, the simulated water vapor content biases, and the inadequate physical parameterizations in the CCLM model. A parallel 0.44° simulation is conducted and the comparison results show some added value introduced by the higher resolution 0.22° simulation. As a result, the CCLM model could be an adequate member for the next stage of the CORDEX-EA project, while further studies should be encouraged.     

Low-frequency sea-level variability in the South China Sea and its relationship to ENSO

Sea-level variability in the South China Sea was investigated based on satellite altimetry, tide-gauge data, and temperature and salinity climatology. The altimetric sea-level results clearly reveal three distinct amphidromes associated with the annual cycle. The annual sea level is higher in fall/winter in the coast and shelf region and lower in summer/fall in the central sea, agreeing well with independent tide-gauge data. Averaged over the deep basin (bottom depth?>?2,000 m), the annual cycle can be approximately accounted for by the steric height relative to 700 db. Significant interannual sea-level change is observed from altimetry and tide-gauge data. The interannual and longer-term sea-level variability in the altimetric data is negatively correlated (significant at the 95% confidence level) with the El Niño - Southern Oscillation (ENSO), attributed in part to the steric height change. The altimetric sea-level rise rate is 1.0 cm/year for the period from 1993 to 2001, which is consistent with the rate derived from coastal tide-gauge data and approximately accountable for by the steric height calculated relative to 700 db. The tide-gauge sea-level (steric height) rise rate of 1.05 (0.9) cm/year from 1993 to 2001 is much larger than that of 0.22 (0.12) cm/year for the period from 1979 to 2001, implying the sensitivity to the length of data as a result of the decadal variability. Potential roles of the ENSO in the interannual and longer-term sea-level variability are discussed in terms of regional manifestations such as the ocean temperature and salinity.     

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。     

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.     

A high-resolution ocean-atmosphere coupled downscaling of the present climate over California

A fully coupled regional ocean-atmosphere model system that consists of the regional spectral model and the regional ocean modeling system for atmosphere and ocean components, respectively, is applied to downscale the present climate (1985–1994) over California from a global simulation of the Community Climate System Model 3.0 (CCSM3). The horizontal resolution of the regional coupled modeling system is 10 km, while that of the CCSM3 is at a spectral truncation of T85 (approximately 1.4°). The effects of the coupling along the California coast in the boreal summer and winter are highlighted. Evaluation of the sea surface temperature (SST) and 2-m air temperature climatology shows that alleviation of the warm bias along the California coast in the global model output is clear in the regional coupled model run. The 10-m wind is also improved by reducing the northwesterly winds along the coast. The higher resolution coupling effect on the temperature and specific humidity is the largest near the surface, while the significant impact on the wind magnitude appears at a height of approximately 850-hPa heights. The frequency of the Catalina Eddy and its duration are increased by more than 60 % in the coupled downscaling, which is attributed to enhanced offshore sea-breeze. Our study indicates that coupling is vital to regional climate downscaling of mesoscale phenomena over coastal areas.     

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