Uncertainty in land surface temperature simulation over China by CMIP3/CMIP5 models

In this paper, China-based observations are used to evaluate the performance of 24 CMIP3 (phase 3 of the Coupled Model Intercomparison Project) and 10 CMIP5 models in simulating land surface temperature (LST). It is found that all models can generally reproduce the climatology patterns of LST averaged during the period from 1960 to 1999. Further analyses of the regional features of LST show that the discrepancies between the observations and the simulations are smaller in Southwest and East China. Moreover, these models overestimate the temperatures in almost all areas, particularly in July. Although many models have large biases relative to the observations, the spread of the model results is large (i.e., >22 °C in Northwest and Northeast China). For the interannual variations, neither the individual models nor the multi-model mean has a remarkable positive correlation to the observations in the selected subregions. However, most models can capture geographic features during trend evaluations. A multi-model ensemble is believed to be an effective way to limit uncertainties, but the results suggest that its efficiency is restricted to simulating the LST trend. Examination of the surface energy budget indicated that the modeled discrepancies of net shortwave radiation and surface sensible heat flux may be responsible for the LST results, especially in July. It is concluded that the ability of current models in simulating LST over China is still a significant challenge. The spread of the models is large in simulating the climatology, interannual variation, and trend of LSTs. In general, the magnitudes of the spread may be as large as the magnitudes of the observations. Additionally, it is found that multi-model ensembles do not simulate LST with any more skill. Therefore, more work must focus on the limitations of the models' uncertainties in land surface research.     

Narrowing the surface temperature range in CMIP5 simulations over the Arctic

Theoretical and Applied Climatology - Much uncertainty exists in reproducing Arctic temperature using different general circulation models (GCMs). Therefore, evaluating the performance of GCMs in...     

WRF模式对中国夏季降水的动力降尺度模拟研究

为了解国家气候中心第二代季节预测模式系统（BCCv2）预测产品在重庆地区的动力降尺度效果,利用WRF模式对BCCv2的2016年汛期预测数据进行动力降尺度试验,对比了动力降尺度前后预测的重庆地区汛期平均降水的差异及采用不同边界层参数化方案对降水预测的影响。试验结果表明,动力降尺度能较好地改善BCCv2对重庆地区汛期降水预测整体偏少的情况,且在降水空间分布特征上与观测更加接近。对比采用不同边界层参数化方案（MYJ、MYNN2、YSU和ACM2）后的降水预测结果可知,YSU方案偏差较小;但从整体看,各方案间差异并不明显。对环流场的偏差分析以及进一步利用松弛逼近法进行的试验表明,动力降尺度能较好地改善BCCv2对青藏高原以南和中国南部地区位势高度预测的正偏差,并能改善降尺度前其对高原南部偏西风水汽输送预测的偏弱,但对两广一带向北水汽输送预测依然较弱;边界场在环流形势预测中的偏差可能与动力降尺度预测的重庆地区汛期降水整体偏少存在联系。

     

秋季北极海冰对中国冬季气温的影响

利用海冰资料、中国地面气候资料、环流特征量资料及NCEP/NCAR再分析资料,研究了秋季北极海冰变化对中国冬季平均气温、日气温变率以及异常低温天气的影响。分析结果表明,秋季北极海冰异常偏多年中国冬季常为暖冬;异常偏少年中国冬季常为冷冬,且异常低温天气出现频率更高,常发生低温灾害事件。秋季北极海冰通过影响后期的北半球极涡、东亚冬季风和西伯利亚高压进而影响中国冬季的平均气温,且通过影响冬季异常强西伯利亚高压的出现频次,影响中国冬季异常低温天气的发生频次。合成分析结果表明,秋季北极海冰异常偏少年的冬季,中国以北亚欧大陆高纬度的偏北风较强,且中国及其以北的中高纬度地区空气异常偏冷,导致极地和高纬度的冷空气易向南爆发,造成中国冬季气温偏低,异常低温天气频发。     

BCC_CSM北极海冰模拟性能的改进对东亚冬季气候模拟的影响

国家气候中心气候系统模式(BCC_CSM)将美国Los Alamos国家实验室发展的海冰模式CICE5.0替代原有的海冰模式SIS,形成一个新版本耦合模式,很好地提高了模式对北极海冰和北极气候的模拟能力.在此基础上,本文评估新耦合模式对1985-2014年东亚冬季气候的模拟性能,检验北极海冰模拟性能的改进对东亚冬季气候...     

The influence of human activity in the Arctic on climate and climate impacts

Human activities in the Arctic are often mentioned as recipients of climate-change impacts. In this paper we consider the more complicated but more likely possibility that human activities themselves can interact with climate or environmental change in ways that either mitigate or exacerbate the human impacts. Although human activities in the Arctic are generally assumed to be modest, our analysis suggests that those activities may have larger influences on the arctic system than previously thought. Moreover, human influences could increase substantially in the near future. First, we illustrate how past human activities in the Arctic have combined with climatic variations to alter biophysical systems upon which fisheries and livestock depend. Second, we describe how current and future human activities could precipitate or affect the timing of major transitions in the arctic system. Past and future analyses both point to ways in which human activities in the Arctic can substantially influence the trajectory of arctic system change.     

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO₂) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO₂, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5–10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970–1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO₂ concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061±0.0036 hPa per %CO₂. Although an increase of 0.61 hPa in NAO for a doubling in CO₂ represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models’ inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.     

Comparing the Arctic climate in Chinese and other CMIP6 models

本研究采用来自耦合模式相互比较项目第六阶段(CMIP6)模式,评估和对比了10个中国模式和27个其他国际模式对北极冬季气候的历史模拟性能.本文的主要目的是展现中国模式对北极气候的模拟能力,并了解其在国际上的模拟水平.结果表明,对于气候态的模拟,中国模式在模拟北极温度场和大气场这些气候学方面与其他国际模式相当.而在趋势方面,中国模式同样和其他国际模式都能很好地模拟出北极变暖的特征.此外,与观测到的环流相比,CMIP6多模式集合平均值(MME)并没有显著的正趋势,这可能是因为外部强迫的作用.     

Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections

The impact of future climate change on the glaciers in the Karakoram and Himalaya (KH) is investigated using CMIP5 multi-model temperature and precipitation projections, and a relationship between glacial accumulation-area ratio and mass balance developed for the region based on the last 30 to 40 years of observational data. We estimate that the current glacial mass balance (year 2000) for the entire KH region is -6.6?±?1 Gta^?1, which decreases about sixfold to -35?±?2 Gta^?1 by the 2080s under the high emission scenario of RCP8.5. However, under the low emission scenario of RCP2.6 the glacial mass loss only doubles to -12?±?2 Gta^?1 by the 2080s. We also find that 10.6 and 27 % of the glaciers could face ‘eventual disappearance’ by the end of the century under RCP2.6 and RCP8.5 respectively, underscoring the threat to water resources under high emission scenarios.     

The influence of the Arctic Oscillation on winter temperatures in Iran

Summary The impact of the Arctic Oscillation (AO) on the winter surface air temperature (SAT) over Iran is demonstrated. Winter SAT data for 50 years (1951–2000) are analyzed for the negative and the positive AO phases. Using the Median Sequential Correlation Analysis (MSCA) technique it is shown that the winter SAT is negatively correlated to the winter AO index for most parts of Iran. The winter AO index accounts for about 14% to 46% of the winter SAT variance. The positive (negative) SAT anomaly is found to be associated with the onset of the negative (positive) phase. The overall probability of below long-term mean temperature during the positive and the negative phases are estimated to be around 70% and 25%, respectively. For the negative phase, westerly winds that originate from the warm Atlantic regions increase over Iran and consequently positive temperature anomalies are found across the country. The positive AO phase is accompanied by northerly winds that allow continental polar and arctic air masses to move into Iran, producing below normal temperatures. The summer AO is found to explain about 25–32% of the winter SAT variance in Iran. The reason for this is explained by the significant correlation (+0.38) between the summer and the following winter AO indices. These results indicate that the summer climate is linked to changes in atmospheric circulation which persist through to the following autumn and winter.     

A transition from CMIP3 to CMIP5 for climate information providers: the case of surface temperature over eastern North America

The release of new data constituting the Coupled Model Intercomparison Project—Phase 5 (CMIP5) database is an important event in both climate science and climate services issues. Although users’ eagerness for a fast transition from CMIP3 to CMIP5 is expected, this change implies some challenges for climate information providers. The main reason is that the two sets of experiments were performed in different ways regarding radiative forcing and hence continuity between both datasets is partially lost. The objective of this research is to evaluate a metric that is independent of the amount and the evolution of radiative forcing, hence facilitating comparison between the two sets for surface temperature over eastern North America. The link between CMIP3 and CMIP5 data sets is explored spatially and locally (using the ratio of local to global temperatures) through the use of regional warming patterns, a relationship between the grid-box and the global mean temperature change for a certain time frame. Here, we show that local to global ratios are effective tools in making climate change information between the two sets comparable. As a response to the global mean temperature change, both CMIP experiments show very similar warming patterns, trends, and climate change uncertainty for both winter and summer. Sensitivity of the models to radiative forcing is not assessed. Real inter-model differences remain the largest source of uncertainty when calculating warming patterns as well as spatially-based patterns for the pattern scaling approach. This relationship between the datasets, which may escape users when they are provided with a single radiative forcing pathway, needs to be stressed by climate information providers.     

Regional and seasonal intercomparison of CMIP3 and CMIP5 climate model ensembles for temperature and precipitation

Regional and seasonal temperature and precipitation over land are compared across two generations of global climate model ensembles, specifically, CMIP5 and CMIP3, through historical twentieth century skills and multi-model agreement, and twenty first century projections. A suite of diagnostic and performance metrics, ranging from spatial bias or model-consensus maps and aggregate time series plots, to measures of equivalence between probability density functions and Taylor diagrams, are used for the intercomparisons. Pairwise and multi-model ensemble comparisons were performed for 11 models, which were selected based on data availability and resolutions. Results suggest little change in the central tendency or variability or uncertainty of historical skills or consensus across the two generations of models. However, there are regions and seasons, at different levels of aggregation, where significant changes, performance improvements, and even degradation in skills, are suggested. The insights may provide directions for further improvements in next generations of climate models, and in the meantime, help inform adaptation and policy.     

The influence of the Madden-Julian oscillation on high-latitude surface air temperature during boreal winter

By analyzing NCEP-NCAR reanalysis daily data for 1979–2016, the modulation by Madden-Julian Oscillation (MJO) of the wintertime surface air temperature (SAT) over high latitude is examined. The real-time multivariate MJO (RMM) index, which divides the MJO into eight phases, is used. It is found that a significantly negative SAT anomaly over the northern high latitude region of (180°–60 °W, 60°–90 °N) lags the MJO convection for 1∼2 weeks in phase 3, in which the enhanced convective activity exists over the Indian Ocean. While a significantly positive SAT anomaly appears over the same region following the MJO phase 7, as the tropical heating shows an opposite sign. Analysis of the anomalous circulation indicates that the observed SAT signal is probably a result of the northeastward propagating Rossby wave train triggered by MJO-related tropical forcing through Rossby wave energy dispersion. By using an anomalous atmospheric general circulation model (AGCM), the significant effect of tropical forcing on organizing the extratropical circulation anomaly is confirmed. Analysis of a temperature tendency equation further reveals that the intraseasonal SAT anomaly is primarily attributed to the advection of the mean temperature by the wind anomaly associated with the anomalous circulation of the MJO-related variability.     

CMIP5多模式集合对江苏省气候变化模拟评估及情景预估

利用中国气象局所属的2 400余个台站观测资料制作的分辨率为0.25°×0.25°数据集中的气温、降水量资料评估了CMIP5中17个模式对于1961—2004年江苏省气温和降水量空间分布特征的模拟能力,筛选出了5个对江苏省气候特征模拟较好的模式。之后基于5个优选模式集合平均的结果预估了3种典型浓度路径(Representative Concentration Pathways,RCPs)下江苏省2006—2100年的气温和降水量变化趋势。结果表明:(1)全球耦合气候模式对江苏省的气温和降水量空间分布特征具有一定的模拟能力,并且模式集合平均的气温和降水量与观测资料的空间相关系数分别为0.85和0.93;(2)在低浓度路径(RCP2.6)、中浓度路径(RCP4.5)和高浓度路径(RCP8.5)3种温室气体排放情景下,江苏省2006—2100年的地表温度均呈现明显的增温趋势,并且苏北的增温幅度要高于苏南;(3)3种温室气体排放情景下,江苏省未来百年降水量均呈现出北方增多南方减少的趋势;(4)未来百年江苏省降水量随气温变化的趋势并不稳定,RCP2.6和RCP4.5情景下降水量随气温的升高而增加,而RCP8.5情景下降水量随气温的增加而减少。     

ENSO phase-locking to the boreal winter in CMIP3 and CMIP5 models

In this study, the El Nino-Southern Oscillation (ENSO) phase-locking to the boreal winter in CMIP3 and CMIP5 models is examined. It is found that the models that are poor at simulating the winter ENSO peak tend to simulate colder seasonal-mean sea-surface temperature (SST) during the boreal summer and associated shallower thermocline depth over the eastern Pacific. These models tend to amplify zonal advection and thermocline depth feedback during boreal summer. In addition, the colder eastern Pacific SST in the model can reduce the summertime mean local convective activity, which tends to weaken the atmospheric response to the ENSO SST forcing. It is also revealed that these models have more serious climatological biases over the tropical Pacific, implying that a realistic simulation of the climatological fields may help to simulate winter ENSO peak better. The models that are poor at simulating ENSO peak in winter also show excessive anomalous SST warming over the western Pacific during boreal winter of the El Nino events, which leads to strong local convective anomalies. This prevents the southward shift of El Nino-related westerly during boreal winter season. Therefore, equatorial westerly is prevailed over the western Pacific to further development of ENSO-related SST during boreal winter. This bias in the SST anomaly is partly due to the climatological dry biases over the central Pacific, which confines ENSO-related precipitation and westerly responses over the western Pacific.     

The nonlinear association between the Arctic Oscillation and North American winter climate

Nonlinear projections of the Arctic Oscillation (AO) index onto North American winter (December–March) 500-mb geopotential height (Z500) and surface air temperature (SAT) anomalies reveal a pronounced asymmetry in the atmospheric patterns associated with positive and negative phases of the AO. In a linear view, the Z500 anomaly field associated with positive AO resembles a positive North Atlantic Oscillation pattern with statistically significant positive and negative anomalies stretching zonally into central-eastern USA and Canada, respectively, resulting in a cold climate anomaly over northeastern and eastern Canada, Alaska and the west coast of USA, and a warm climate anomaly over the rest of the continent. By contrast, the nonlinear behavior, mainly a quadratic association with AO, which is most apparent when the amplitude of the AO index is large, has the same spatial pattern and sign for both positive and negative values of the index. The nonlinear pattern reveals negative Z500 anomalies over the west coast of USA and the North Atlantic and positive Z500 anomalies at higher latitudes centered over the Gulf of Alaska and northeastern Canada accompanied by cooler than normal climate over the USA and southwestern Canada and warmer than normal climate over other regions of the continent. A similar analysis is conducted on the data from the Canadian Center for Climate Modelling and Analysis second generation coupled general circulation model. The nonlinear patterns of North American Z500 and SAT anomalies associated with the AO in the model simulation are generally consistent with the observational results, thereby confirming the robustness of the nonlinear behavior of North American winter climate with respect to the AO in a climate simulation that is completely independent of the observations.     

The influence of clouds on surface UV erythemal irradiance

The purpose of this study is to examine the effect of clouds on the ultraviolet erythemal irradiance. The study was developed at three stations in the Iberian Peninsula: Madrid and Murcia, using data recorded in the period 2000–2001, and Zaragoza, using data recorded in 2001. In order to determine the cloud effect on ultraviolet erythemal irradiance, we considered a cloud modification factor defined as the ratio between the measured values of ultraviolet erythemal irradiance and the corresponding clear-sky ultraviolet erythemal irradiance, which would be expected for the same time period and atmospheric conditions. The dependence of this cloud modification factor on total cloud amount, cloud type and solar elevation angle was investigated. The results suggest that the effect of cloud on ultraviolet erythemal irradiance can be parameterized in a simple way in terms of the cloud amount. Our results suggest that the same cloud modification factor model can be used at the three analysed locations estimating the ultraviolet erythemal irradiance with mean bias deviation (MBD) in the range of the expected experimental errors. This cloud modification factor is lower than that associated to the whole solar spectral range, indicating that the attenuation for the ultraviolet erythemal irradiance is lower than that associated to other solar spectral ranges. The cloud modification factor for ultraviolet erythemal irradiance presents dependence with solar elevation, with opposite dependencies with solar elevation for overcast and partial cloud cover conditions, a fact that can be explained in terms of the influence of reflection-enhancement of the ultraviolet irradiance in the last case. Concerning the influence of cloud type, a limited study of two cloud categories, low and medium level and high level, indicated that for overcast conditions, lower clouds presents an attenuation of ultraviolet erythemal irradiance 20% greater than that associated to high level clouds.