CMIP5模式对西太平洋副热带高压的模拟和预估

利用国际耦合模式比较计划第五阶段（CMIP5）26个模式的模拟结果,从空间分布和振幅变化、年际周期及年代际趋势等方面,初步评估了CMIP5模式对西太平洋副热带高压（副高）的模拟能力。在此基础上,还对未来不同典型浓度路径（RCPs）情景下副高的可能变化给出了定性的预估。CMIP5模式历史试验结果显示,大多数模式对500 hPa位势高度气候平均值的模拟有明显误差,这主要是由于模式对热带印度洋和西太平洋地区海表温度（SST）的模拟普遍较观测值低,从而导致模式对副高的模拟能力有限。但大多数模式对高度场和纬向风场变化的空间形态与振幅都有较强的模拟能力。因此,通过用NCEP/NCAR再分析资料的气候平均值替代CMIP5模式气候平均值的简单方法,对CMIP5模拟结果进行了订正。经订正后的模式结果均有能力刻画副高指数的历史时间序列,且能够反映出20世纪70年代末期之后,副高面积增大、强度增强和显著西伸的变化趋势。此外,通过对副高指数的长期趋势、年际周期及标准差等的定量评估,注意到CNRM-CM5、FGOALS-g2、FIO-ESM、MIROC-ESM和MPI-ESM-P这5个模式对副高的模拟能力较强。未来气候预估试验中,副高面积和强度均增大,且显著西伸;其线性增长趋势在RCP8.5情景下最高,RCP4.5情景下次之,RCP2.6情景下最弱。有趣的是副高脊线指数在3种排放情景下都没有明显的长期变化趋势。这些结果为选取和利用CMIP5模式进行东亚地区气候变化的归因分析和未来预估提供了一定的科学依据。     

ENSO representation in climate models: from CMIP3 to CMIP5

We analyse the ability of CMIP3 and CMIP5 coupled ocean–atmosphere general circulation models (CGCMs) to simulate the tropical Pacific mean state and El Niño-Southern Oscillation (ENSO). The CMIP5 multi-model ensemble displays an encouraging 30 % reduction of the pervasive cold bias in the western Pacific, but no quantum leap in ENSO performance compared to CMIP3. CMIP3 and CMIP5 can thus be considered as one large ensemble (CMIP3 + CMIP5) for multi-model ENSO analysis. The too large diversity in CMIP3 ENSO amplitude is however reduced by a factor of two in CMIP5 and the ENSO life cycle (location of surface temperature anomalies, seasonal phase locking) is modestly improved. Other fundamental ENSO characteristics such as central Pacific precipitation anomalies however remain poorly represented. The sea surface temperature (SST)-latent heat flux feedback is slightly improved in the CMIP5 ensemble but the wind-SST feedback is still underestimated by 20–50 % and the shortwave-SST feedbacks remain underestimated by a factor of two. The improvement in ENSO amplitudes might therefore result from error compensations. The ability of CMIP models to simulate the SST-shortwave feedback, a major source of erroneous ENSO in CGCMs, is further detailed. In observations, this feedback is strongly nonlinear because the real atmosphere switches from subsident (positive feedback) to convective (negative feedback) regimes under the effect of seasonal and interannual variations. Only one-third of CMIP3 + CMIP5 models reproduce this regime shift, with the other models remaining locked in one of the two regimes. The modelled shortwave feedback nonlinearity increases with ENSO amplitude and the amplitude of this feedback in the spring strongly relates with the models ability to simulate ENSO phase locking. In a final stage, a subset of metrics is proposed in order to synthesize the ability of each CMIP3 and CMIP5 models to simulate ENSO main characteristics and key atmospheric feedbacks.     

Dynamic sea level changes following changes in the thermohaline circulation

Using the coupled climate model CLIMBER-3, we investigate changes in sea surface elevation due to a weakening of the thermohaline circulation (THC). In addition to a global sea level rise due to a warming of the deep sea, this leads to a regional dynamic sea level change which follows quasi-instantaneously any change in the ocean circulation. We show that the magnitude of this dynamic effect can locally reach up to ~1 m, depending on the initial THC strength. In some regions the rate of change can be up to 20–25 mm/yr. The emerging patterns are discussed with respect to the oceanic circulation changes. Most prominent is a south-north gradient reflecting the changes in geostrophic surface currents. Our results suggest that an analysis of observed sea level change patterns could be useful for monitoring the THC strength.     

Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models简

Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.     

The Indian Ocean subtropical dipole mode simulated in the CMIP3 models

Using observation data and outputs from the “twentieth-century climate in coupled models” (20c3m) control runs of coupled general circulation models submitted to the Coupled Model Intercomparison Project, phase 3 (CMIP3), the ability of CMIP3 models to simulate the Indian Ocean subtropical dipole (IOSD) and its influence on the rainfall anomaly over the southern African region is investigated. Many models simulate the IOSD, but the location and shape of the sea surface temperature anomaly vary among models. This model bias is closely linked to the bias in simulating the anomalous strengthening and southward shift of the subtropical high. Almost all models fail to simulate the rainfall anomaly associated with the IOSD owing to the inaccurate simulation of the location of sea surface temperature and sea level pressure anomalies.     

Heat budget of the south-central equatorial Pacific in CMIP3 models

ABSTRACT Using data from 17 coupled models and nine sets of corresponding Atmospheric Model Intercomparison Project （AMIP） results, we investigated annual and seasonal variation biases in the upper 50 m of the south-central equatorial Pacific, with a focus on the double-ITCZ bias, and examined the causes for the amplitude biases by using heat budget analysis. The results showed that, in the research region, most of the models simulate SSTs that are higher than or similar to observed. The simulated seasonal phase is close to that observed, but the amplitudes of more than half of the model results are larger than or equal to observations. Heat budget analysis demonstrated that strong shortwave radiation in individual atmospheric models is the main factor that leads to high SST values and that weak southward cold advection is an important mechanism for maintaining a high SST. For seasonal circulation, large surface shortwave radiation amplitudes cause large SST amplitudes.     

Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.     

CMIP5模式对未来升温情景下全球陆地生态系统净初级生产力变化的预估

针对《巴黎协定》提出的温控目标,利用耦合模式比较计划第五阶段（CMIP5）模式在RCP2.6、RCP4.5和RCP8.5情景下的模拟结果,初步分析了全球升温情景下陆地生态系统净初级生产力（NPP）相对于参考时段（1986—2005年）的变化,重点分析了1.5℃和2℃升温时NPP相对于参考时段的变化量,并探讨了大气CO₂浓度、气温、降水和辐射的变化及其对NPP变化的影响。CMIP5基于各典型浓度路径模拟的全球陆地生态系统NPP均呈增加趋势,且NPP增加量与升温幅度成正比。在相同的升温幅度下,基于各典型浓度路径模拟的各环境因子和NPP的变化量较为一致。陆地生态系统NPP总量增加主要由大气CO₂浓度上升驱动,其他环境因子的影响相对较弱。中国东南部、非洲中部、美国东南部和亚马孙雨林西部地区NPP增加最明显。NPP变化量的空间格局主要由大气CO₂浓度增加和升温控制,降水和辐射的影响相对较小。具体而言,大气CO₂浓度上升对中低纬度的NPP变化贡献最大,对北方高纬度地区NPP变化贡献较小。温度上升有利于促进北方高纬度地区和青藏高原地区NPP,但对中低纬度地区的NPP有较强的抑制作用。鉴于既有典型浓度路径和地球系统模型的限制,本文对未来升温情景下陆地生态系统NPP的预估仍存在较大的不确定性,需要在未来的研究中进一步改进。     

Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region

One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.     

基于CMIP5模式安徽省植被净初级生产力预估

利用耦合模式比较计划第5阶段（CMIP5）中5个全球气候模式3种典型浓度路径（RCPs）预估结果,基于植被净初级生产力模型,估算安徽省21世纪近期（2018—2030年)、中期（2031—2050年）和远期（2051—2099年）植被净初级生产力及其对气候变化的响应。结果表明：对不同模式在安徽省模拟能力的评估可知,气温以多模式集合模拟效果优于单个模式,MIROC-ESM-CHEM对降水的模拟能力较好。未来安徽省将持续变暖,北部变暖幅度高于南部,其中RCP8.5情景下变暖趋势更显著;全省降水量将增加,南部增加多于北部。随着气候趋于暖湿化,植被净初级生产力总体增加;与基准年相比,21世纪近期增加不明显,中后期显著增加,空间上南部增加总体高于北部。从气候变化响应来看,安徽省植被净初级生产力与降水量和平均气温均显著相关,并且对降水量的响应程度更高。     

Climate of Russia in the 21st century. Part 3. Future climate changes calculated with an ensemble of coupled atmosphere-ocean general circulation CMIP3 models

Probable climate changes in Russia in the 21st century are considered based on the results of global climate simulations with an ensemble of coupled atmosphere-ocean CMIP3 models. The future changes in the surface air temperature, atmospheric pressure, cloud amount, atmospheric precipitation, snow cover, soil water content, and annual runoff in Russia and some of its regions in the early, middle, and late 21st century are analyzed using the A2 scenario of the greenhouse gas and aerosol emission. Future changes in the yearly highest and lowest surface air temperatures and in summer precipitation of high intensity are estimated for Russia. Possible oscillations of the Caspian Sea level associated with the expected global climate warming are estimated. In addition to the estimates of the ensemble mean changes in climatic characteristics, the information about standard deviations and statistical significance of the corresponding climate changes is given.     

A diagnostic study of future evaporation changes projected in CMIP5 climate models

It has been pointed out that climatological-mean precipitation-evaporation difference (P–E) should increase under global warming mainly through the increasing saturation level of moisture. This study focuses on evaporation changes under global warming and their dependency on the direct warming effect, on the basis of future projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Over most of the tropical, subtropical and midlatitude regions, the direct contribution from surface temperature increase is found to dominate the projected increase in evaporation. This contribution is nevertheless offset partially, especially over the oceans, by contributions from weakening surface winds and increasing near-surface relative humidity. Greater warming of surface air than of the sea surface also acts to reduce surface evaporation, by reducing both the exchange coefficient and humidity contrast at the surface. Though generally of secondary importance, this contribution is the dominant factor over the subpolar oceans. Over the polar oceans, the effect of sea-ice retreat dominantly contributes to the evaporation increase in winter, whereas the reduced exchange coefficient and surface humidity contrast coupled with the sea-ice retreat account for most of the response during summertime. Over the continents, changes in the surface exchange coefficient, reflecting changes in soil moisture and vegetation among other factors, are important to modulate the direct effects of the warming and the generally reduced surface air relative humidity.     

Simulation and Projection of the Western Pacific Subtropical High in CMIP5 Models

This work examined the performance of 26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5 （CMIP5） in the simulation of the present-day temporal variability and spatial pattern of the western Pacifi c subtropical high （WPSH）. The results show that most models are able to capture the spatial distribution and variability of the 500-hPa geopotential height and zonal wind fi elds in the western subtropical Pacifi c, but with underestimated mean intensity of the WPSH. The underestimation may be associated with the cold bias of sea surface temperature in the tropical Indian and western Pacifi c oceans in the models. To eliminate the impact of the climatology biases, the climatology of these models is replaced by that of the NCEP/NCAR reanalysis in the verifi cation, and the models reproduce the WPSH’s enhancement and westward extension after the late 1970s. According to assessment of the simulated WPSH indices, it is found that some models （CNRM-CM5, FGOALS-g2, FIO-ESM, MIROC-ESM, and MPI-ESM-P） are better than others in simulating WPSH. Then, the ensemble mean of these better models is used to pro ject the future changes of WPSH under three representative concentration pathway scenarios （RCP8.5, RCP4.5, and RCP2.6）. The WPSH enlarges, strengthens, and extends westward under all the scenarios, with the largest linear growth trend projected in RCP8.5, smallest in RCP2.6, and in between in RCP4.5;while the ridge line of WPSH shows no obvious long-term trend. These results may have implications for the attribution and prediction of climate variations and changes in East Asia.     

Performance of CMIP6 models in simulating the dynamic sea level: Mean and interannual variance

Observational data from satellite altimetry were used to quantify the performance of CMIP6 models in simulating the climatological mean and interannual variance of the dynamic sea level (DSL) over 40°S–40°N. In terms of the mean state, the models generally agree well with observations, and high consistency is apparent across different models. The largest bias and model discrepancy is located in the subtropical North Atlantic. As for simulation of the interannual variance, good agreement can be seen across different models, yet the models present a relatively low agreement with observations. The simulations show much weaker variance than observed, and bias is apparent over the subtropics in association with strong western boundary currents. This nearshore bias is reduced considerably in HighResMIP models. The underestimation of DSL interannual variance is at least partially due to the misrepresentation of ocean processes in the CMIP6 historical simulation with its relatively low resolution. The results identify directions for future model development towards a better understanding of the mean and interannual variability of DSL.摘要本研究采用卫星测高数据与第六次国际耦合模式比较计划 (CMIP6) 海平面动力进行对比, 重点针对40°S–40°N地区的动力海平面 (DSL) , 评估了模式对其平均态与年际变率的综合模拟能力. 结果表明, 对于DSL平均态的模拟, 模式与观测结果非常吻合, 模式之间的差异较小. 其中, 副热带北大西洋是模拟偏差和模式间差异较为显著的区域. 对于DSL年际变率的模拟, 模式之间保持较高的一致性, 但是, 模式与观测结果存在明显差异, 模式普遍低估了DSL的年际方差; 其中, 误差大值区域出现在副热带西边界流附近. 模式分辨率会影响CMIP6对中小尺度海洋过程的重现能力, 这可能是导致CMIP6历史模拟出现误差的原因之一.     

Climate of Russia in the 21st Century. Part 2. Verification of atmosphere-ocean general circulation models CMIP3 for projections of future climate changes

Results of simulation of radiation, cloud cover, surface air temperature, sea-level pressure, and hydrological regime components for Russia with the help of an ensemble of CMIP3 global climate models is analyzed. Despite a large spread among the models, the CMIP3 AOGCM ensemble simulations of the key characteristics of the observed surface climate agree well with observations, anyway in averaging over areas of vast regions, from watersheds of large rivers to the whole of Russia. These means (ensemble-and area-averaged values) often fall into the range of estimates derived from observations. This suggests the existence of uncertainty in the estimates obtained from simulations as well as from observational data. Comparison of different-generation models demonstrates a gradual improvement of the AOGCM simulation of surface climate characteristics. In general, the averaging over the CMIP3 AOGCM ensemble allows us to state that the ensemble is suitable for estimates of future climate changes.     

Assessment of CMIP3 climate models and projected changes of precipitation and temperature in the Yangtze River Basin, China

The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011–2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from ?21 to 28.5?mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models.     

Implications of CMIP3 model biases and uncertainties for climate projections in the western tropical Pacific

Regional climate projections in the Pacific region are potentially sensitive to a range of existing model biases. This study examines the implications of coupled model biases on regional climate projections in the tropical western Pacific. Model biases appear in the simulation of the El Niño Southern Oscillation, the location and movement of the South Pacific Convergence Zone, rainfall patterns, and the mean state of the ocean–atmosphere system including the cold tongue bias and erroneous location of the edge of the Western Pacific warm pool. These biases are examined in the CMIP3 20th century climate models and used to provide some context to the uncertainty in interpretations of regional-scale climate projections for the 21st century. To demonstrate, we provide examples for two island nations that are located in different climate zones and so are affected by different biases: Nauru and Palau. We discuss some of the common approaches to analyze climate projections and whether they are effective in reducing the effect of model biases. These approaches include model selection, calculating multi model means, downscaling and bias correcting.     

Novel dynamical indices for the variations of the western Pacific subtropical high based on three-pattern decomposition of global atmospheric circulation in a warming climate

Previous studies have often used the 500 hPa geopotential height to define indices of the western Pacific subtropical high (WPSH). However, some studies reported that global warming caused a significant increase in geopotential height, particularly at the middle and lower latitudes, leading artificial results about long-term trend of the WPSH. To avoid the spurious signals resulting from global warming, this study first redefines the area, intensity, westward ridge point and ridge line indices of the WPSH by adopting the stream function R of horizontal circulation in the three-pattern decomposition of global atmospheric circulation (3P-DGAC). Subsequently, the climatic characteristics of the WPSH in summer are investigated by applying the new indices based on four reanalysis datasets. The results show that the circulation features of the WPSH could be revealed by the stream function R in 3P-DGAC. Moreover, the rain belt over East Asia is located at the northwest periphery of the zero-value isoline of the stream function R. We conclude that the climatological average WPSH is contracted and retreated eastward during 1979–2018 relative to 1948–1978. Nevertheless, by analyzing interdecadal changes of the time series of the new indices during 1948–2018, we find that area and intensity indices decrease with time before the end of 1970s and increase slightly with time after the end of 1970s, the western ridge point index moves eastward with time before the end of the 1970s and moves westward slightly with time after the end of 1970s, as well as there is no obvious interdecadal variations in the ridge line index. Because of the evident dynamical meaning, the stream function R in 3P-DGAC can be used as an objective indicator to describe the interdecadal variation of the WPSH under global warming.

     

Simulation of tropical cyclone activity over the western North Pacific based on CMIP5 models

Based on the Coupled Model Inter-comparison Project 5 (CMIP5) models, the tropical cyclone (TC) activity in the summers of 1965–2005 over the western North Pacific (WNP) is simulated by a TC dynamically downscaling system. In consideration of diversity among climate models, Bayesian model averaging (BMA) and equal-weighed model averaging (EMA) methods are applied to produce the ensemble large-scale environmental factors of the CMIP5 model outputs. The environmental factors generated by BMA and EMA methods are compared, as well as the corresponding TC simulations by the downscaling system. Results indicate that BMA method shows a significant advantage over the EMA. In addition, impacts of model selections on BMA method are examined. To each factor, ten models with better performance are selected from 30 CMIP5 models and then conduct BMA, respectively. As a consequence, the ensemble environmental factors and simulated TC activity are similar with the results from the 30 models’ BMA, which verifies the BMA method can afford corresponding weight for each model in the ensemble based on the model’s predictive skill. Thereby, the existence of poor performance models will not particularly affect the BMA effectiveness and the ensemble outcomes are improved. Finally, based upon the BMA method and downscaling system, we analyze the sensitivity of TC activity to three important environmental factors, i.e., sea surface temperature (SST), large-scale steering flow, and vertical wind shear. Among three factors, SST and large-scale steering flow greatly affect TC tracks, while average intensity distribution is sensitive to all three environmental factors. Moreover, SST and vertical wind shear jointly play a critical role in the inter-annual variability of TC lifetime maximum intensity and frequency of intense TCs.