Transient climate changes in a perturbed parameter ensemble of emissions-driven earth system model simulations

We describe results from a 57-member ensemble of transient climate change simulations, featuring simultaneous perturbations to 54 parameters in the atmosphere, ocean, sulphur cycle and terrestrial ecosystem components of an earth system model (ESM). These emissions-driven simulations are compared against the CMIP3 multi-model ensemble of physical climate system models, used extensively to inform previous assessments of regional climate change, and also against emissions-driven simulations from ESMs contributed to the CMIP5 archive. Members of our earth system perturbed parameter ensemble (ESPPE) are competitive with CMIP3 and CMIP5 models in their simulations of historical climate. In particular, they perform reasonably well in comparison with HadGEM2-ES, a more sophisticated and expensive earth system model contributed to CMIP5. The ESPPE therefore provides a computationally cost-effective tool to explore interactions between earth system processes. In response to a non-intervention emissions scenario, the ESPPE simulates distributions of future regional temperature change characterised by wide ranges, and warm shifts, compared to those of CMIP3 models. These differences partly reflect the uncertain influence of global carbon cycle feedbacks in the ESPPE. In addition, the regional effects of interactions between different earth system feedbacks, particularly involving physical and ecosystem processes, shift and widen the ESPPE spread in normalised patterns of surface temperature and precipitation change in many regions. Significant differences from CMIP3 also arise from the use of parametric perturbations (rather than a multimodel ensemble) to represent model uncertainties, and this is also the case when ESPPE results are compared against parallel emissions-driven simulations from CMIP5 ESMs. When driven by an aggressive mitigation scenario, the ESPPE and HadGEM2-ES reveal significant but uncertain impacts in limiting temperature increases during the second half of the twenty-first century. Emissions-driven simulations create scope for development of errors in properties that were previously prescribed in coupled ocean–atmosphere models, such as historical CO₂ concentrations and vegetation distributions. In this context, historical intra-ensemble variations in the airborne fraction of CO₂ emissions, and in summer soil moisture in northern hemisphere continental regions, are shown to be potentially useful constraints, subject to uncertainties in the relevant observations. Our results suggest that future climate-related risks can be assessed more comprehensively by updating projection methodologies to support formal combination of emissions-driven perturbed parameter and multi-model earth system model simulations with suitable observational constraints. This would provide scenarios underpinned by a more complete representation of the chain of uncertainties from anthropogenic emissions to future climate outcomes.     

Summertime inter-annual temperature variability in an ensemble of regional model simulations: analysis of the surface energy budget

The inter-annual variability in monthly mean summer temperatures derived from nine different regional climate model (RCM) integrations is investigated for both the control climate (1961–1990) and a future climate (2071–2100) based on A2 emissions. All regional model integrations, carried out in the PRUDENCE project, use the same boundaries of the HadAM3H global atmospheric model. Compared to the CRU TS 2.0 observational data set most RCMs (but not all) overpredict the temperature variability significantly in their control simulation. The behaviour of the different regional climate models is analysed in terms of the surface energy budget, and the contributions of the different terms in the surface energy budget to the temperature variability are estimated. This analysis shows a clear relation in the model ensemble between temperature variability and the combined effects of downward long wave, net short wave radiation and evaporation (defined as F). However, it appears that the overestimation of the temperature variability has no unique cause. The effect of short-wave radiation dominates in some RCMs, whereas in others the effect of evaporation dominates. In all models the temperature variability and F increase when imposing future climate boundary conditions, with particularly high values in central Europe.     

一次黑潮海洋锋强迫下的蒸发波导突变性与非均匀性的观测与模拟研究

蒸发波导是影响海上雷达系统探测性能的主导机制,海表温度（SST）锋带来的蒸发波导非均匀性和突变性具有重要的研究价值。2018年春季航次“海气相互作用观测试验”,曾两次穿越黑潮海域获取了珍贵的观测资料。在此基础上,结合欧洲中期天气预报中心（ECMWF）再分析资料（ERA-Interim）和HYSPLIT（Hybrid Single Particle Lagrangian Integrated Trajectories）气块轨迹溯源,分离出两个重要的走航观测时段。S1段（持续约21 h）气流从暖海水区吹向冷海水区,以稳定层结为主,其间因黑潮海洋锋的存在,气流由黑潮主体的暖水区吹向大陆冷海区时,形成具有强逆温层的海洋边界层,并伴随海雾的生成,导致此处蒸发波导高度突降为0。此后为持续近66 h的S2段,气流由冷海水区吹向暖海水区,以近中性弱不稳定层结为主,蒸发波导高度基本维持在12 m高度。数值模拟结果表明,模拟时段内的黑潮海洋锋区,蒸发波导高度突变性和非均匀性始终存在,且伴随暖海水吹向冷海水的锋区突变性更强。黑潮海洋锋对蒸发波导的这种天气尺度强迫作用的加强与层结稳定度的突变和海雾的生成有关。      

Volcanic ash over the Russian Federation territory after the volcanic eruption in Iceland on April 14, 2010 from the data of model simulations and observations

After the volcanic eruption in Iceland on April 14, 2010, the volcanic ash cloud spread over Europe including Russia, that resulted in the air traffic collapse for several days. Presented are the results of computations of the volcanic ash spreading obtained with the FLEXPART Lagrangian dispersion model, as well as the results of the lidar sounding over Troitsk (Moscow region). The obtained model and experimental results agree well with each other and indicate the existence of settling layer of volcanic ash at the height of 4?C6 km, that is corroborated by the data of observations in Europe. The largest uncertainty in the model computations is caused by the lack of information on the volume of the emission of micron particles transported with the wind to the large distance. The comparison of model results with the observational data can enable to correct the source function and to obtain more realistic estimates of volcanic ash concentrations, that is a key factor of the air traffic control.     

Studying the showers and thunderstorms on the territory of Russia using the numerical model of convective cloud and the reanalysis data

The computation of thunderstorm and shower activity on the territory of Russia during the warm period (June–August) of 1981–2000 for four observation times (00:00, 06:00, 12:00, and 18:00) is carried out using the local convective cloud model (CCM) and the ERA-40 reanalysis data on the vertical distribution of temperature and humidity. The spatial grid with the resolution of 2.5 × 2.5° is used for the computation. Collected and analyzed are the long-term (1936–1965) in situ data on the distribution of the number of days with the thunderstorm on the territory of Russia using the observational data from the ground-based meteorological stations (about 600 stations located in different regions). As a result, the distribution of the number of days with the thunderstorm and with the convective precipitation on the territory of Russia is plotted and analyzed. It agrees on the whole with the observed data. It is demonstrated that the number of days with the thunderstorm and with the convective precipitation correlate well with each other, that also corresponds to the observational data. It is shown that CCM is applicable to the simulation of cloud convection and associated phenomena.     

Convective and stratiform precipitation characteristics in an ensemble of regional climate model simulations

We apply a recently proposed algorithm for disaggregating observed precipitation data into predominantly convective and stratiform, and evaluate biases in characteristics of parameterized convective (subgrid) and stratiform (large-scale) precipitation in an ensemble of 11 RCM simulations for recent climate in Central Europe. All RCMs have a resolution of 25 km and are driven by the ERA-40 reanalysis. We focus on mean annual cycle, proportion of convective precipitation, dependence on altitude, and extremes. The results show that characteristics of total precipitation are often better simulated than are those of convective and stratiform precipitation evaluated separately. While annual cycles of convective and stratiform precipitation are reproduced reasonably well in most RCMs, some of them consistently and substantially overestimate or underestimate the proportion of convective precipitation throughout the year. Intensity of convective precipitation is underestimated in all RCMs. Dependence on altitude is also simulated better for stratiform and total precipitation than for convective precipitation, for which several RCMs produce unrealistic slopes. Extremes are underestimated for convective precipitation while they tend to be slightly overestimated for stratiform precipitation, thus resulting in a relatively good reproduction of extremes in total precipitation amounts. The results suggest that the examined ensemble of RCMs suffers from substantial deficiencies in reproducing precipitation processes and support previous findings that climate models’ errors in precipitation characteristics are mainly related to deficiencies in the representation of convection.     

A comparative study of the observations of high clouds and simulations by an atmospheric general circulation model

The importance of clouds in the upper troposphere (cirrus) for the sensitivity of the Earth's climate e.g., requires that these clouds be modeled accurately in general circulation model (GCM) studies of the atmosphere. Bearing in mind the lack of unambiguous quantitative information on the geographical distribution and properties of high clouds, the simulated distribution of upper tropospheric clouds in a spectral GCM is compared with several satellite-derived data-sets that pertain to high clouds only, for both winter and summer seasons. In the model, clouds are assumed to occupy an entire gridbox whenever the relative humidity exceeds 99%: otherwise the grid box is assumed to be free of cloud. Despite the simplicity of the cloud prediction scheme, the geographical distribution of the maxima in the model's upper tropospheric cloud cover coincides approximately with the regions of the observed maxima in the high cloud amount and their frequency of occurrence (e.g., intertropical convergence zone and the monsoon areas). These areas exhibit a minimum in the outgoing longwave radiation (OLR; Nimbus-7) and are also coincident with regions of heavy precipitation. The model, with its relatively simple cloud formation scheme, appears to capture the principal large-scale features of the tropical convective processes that are evident in the satellite and precipitation datasets, wherein the intense, upward motion is accompanied by condensation and the spreading of thick upper tropospheric layers of high relative humidity and cloudiness in the vicinity of the tropical rainbelt regions.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted.     

Detection and attribution of anthropogenic forcing to diurnal temperature range changes from 1950 to 1999: comparing multi-model simulations with observations

Observations show that the surface diurnal temperature range (DTR) has decreased since 1950s over most global land areas due to a smaller warming in maximum temperatures (T _max) than in minimum temperatures (T _min). This paper analyzes the trends and variability in T _max, T _min, and DTR over land in observations and 48 simulations from 12 global coupled atmosphere-ocean general circulation models for the later half of the 20th century. It uses the modeled changes in surface downward solar and longwave radiation to interpret the modeled temperature changes. When anthropogenic and natural forcings are included, the models generally reproduce observed major features of the warming of T _max and T _min and the reduction of DTR. As expected the greenhouse gases enhanced surface downward longwave radiation (DLW) explains most of the warming of T _max and T _min while decreased surface downward shortwave radiation (DSW) due to increasing aerosols and water vapor contributes most to the decreases in DTR in the models. When only natural forcings are used, none of the observed trends are simulated. The simulated DTR decreases are much smaller than the observed (mainly due to the small simulated T _min trend) but still outside the range of natural internal variability estimated from the models. The much larger observed decrease in DTR suggests the possibility of additional regional effects of anthropogenic forcing that the models can not realistically simulate, likely connected to changes in cloud cover, precipitation, and soil moisture. The small magnitude of the simulated DTR trends may be attributed to the lack of an increasing trend in cloud cover and deficiencies in charactering aerosols and important surface and boundary-layer processes in the models.     

协调大集合模拟下全球海表面温度对北极对流层早冬增暖的影响

本文使用六个不同的最新大气模式进行了协调数值集合实验,评估和量化了全球海表面温度(SST)对1982-2014年冬季早期北极变暖的影响.本研究设计了两组实验:在第一组(EXP1)中,将OISSTv2逐日变化的海冰密集度和SST数据作为下边界强迫场;在第二组(EXP2)中,将逐日变化的SST数据替换为逐日气候态.结果表明...     

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.     

利用卫星微波观测亮温与云辐射模拟亮温的台风定位分析

极轨气象卫星S-NPP、MetOp-A和FY-3B上搭载的微波湿度计观测资料可以反映出台风周围水汽和云雨结构。本文使用权重函数峰值在800 hPa附近的微波湿度计通道观测资料和ERA5再分析资料全天空模拟亮温,以飓风Sandy和Isaac为例,对用方位谱台风中心位置定位方法得到的观测和模拟中心位置进行了比较。利用下午星S-NPP搭载的先进技术微波探测仪(Advanced Technology Microwave Sounder, ATMS)和上午星MetOp-A搭载的微波湿度计(Microwave Humidity Sounder, MHS)观测亮温得到的飓风Sandy(Isaac)中心位置与最佳路径平均相差35.8 km(32.9 km),但用ERA5全天空模拟亮温得到的飓风Sandy(Isaac)中心位置与最佳路径平均相差73.3 km(82.1 km)。若按照热带风暴和台风等级来划分,ATMS和MHS观测和模拟亮温得到的台风中心位置与最佳路径的平均距离对热带风暴分别是36.5 km和105.9 km,对台风分别是25.8 km和56.4 km。若用FY-3B搭载的微波湿度计(以M...     

深圳单点气温的时间滞后集合预报研究

利用欧洲中心TL799 L91模式在深圳的单点气温预报数据和深圳本地的气温观测数据,对比分析了时间滞后集合预报方法与传统确定性预报的预报能力.结果表明:(1)TL799 L91 模式提供的确定性预报对于深圳单点气温有一定预报能力,它的预报误差总体上有随预报提前量增加而增加的趋势,但最近时次的确定性预报并不一定是最佳的预报;(2)时间滞后集合预报总体上优于确定性预报,而且参与集合的成员数量越多则预报准确率大体上越高.所以,时间滞后集合预报可在一定程度上改进单点气温的预报质量,是充分利用更早起报时刻数值预报价值的一种有效途径.     

Multi-criterion model ensemble of CMIP5 surface air temperature over China

Theoretical and Applied Climatology - The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the...     

Assessment of surface drag coefficient parametrizations based on observations and simulations using the Weather Research and Forecasting model

海气界面动量交换对台风发展起着重要作用,其估算公式依赖于拖曳系数。本文利用观测和台风模拟试验对八种拖曳系数参数化方案进行系统的评估。结果表明,相对于早期的参数化方案,近些年提出的参数化方案对拖曳系数的描述有了显著的改进,主要体现在高风速条件下。不同的拖曳系数参数化方案对超强台风"海燕"的模拟路径几乎没有影响,但是对其强度、尺寸和结构的模拟结果有显著影响。     

Analysis of precipitation extremes in an ensemble of transient regional climate model simulations for the Rhine basin

A non-stationary index-flood model was used to analyse the 1-day summer and 5-day winter precipitation maxima in the Rhine basin in an ensemble of 15 transient regional climate model (RCM) simulations. It is assumed that the seasonal precipitation maxima follow a generalized extreme value (GEV) distribution with time varying parameters. The index-flood assumption implies that the dispersion coefficient (the ratio of the scale and the location parameters) and the shape parameter are constant over predefined regions, while the location parameter varies within these regions. A comparison with the estimates from gridded observations shows that these GEV parameters are too large in the summer season, while there is a large overestimation of the location parameter and underestimation of the dispersion coefficient in winter. However, a large part of the biases in the summer season might be due to the low number of stations used for gridding the observations. Though there is considerable variation in the changes of the extreme value distributions among the RCM simulations, common tendencies can be identified. In summer, large quantiles increase as a consequence of an increase of the dispersion coefficient, while there is almost no change of low quantiles. In winter, low quantiles increase because of an increase of the location parameter. This effect is, however, counterbalanced by a decrease of the shape parameter in most RCM simulations, resulting in only a slight increase of large quantiles. Departures from the assumed index-flood model were observed in the Alpine region in the south of the basin. This is due to the strong spatial heterogeneity in the dispersion coefficient in a number of RCM simulations and a significant altitude dependence of the trend in the location parameter in winter in five RCM simulations.     

A method to aid in the determination of the sampling size of AGCM ensemble simulations

Historically, the high computational expense of performing lengthy climate simulations has limited the number of possible realizations. Here, we exploit the computational advantage of a recently developed parallel atmospheric general circulation model (AGCM) to determine the number of realizations required to calculate the model's statistics to a specified degree of certainty. Using standard statistical analysis techniques, this minimum ensemble size is found to be highly dependent on which output field is under examination. A strong dependence on location, season and averaging is also revealed. Received: 23 September 1998 / Accepted: 23 July 1999