An evaluation of Arctic cloud and radiation processes during the SHEBA year: simulation results from eight Arctic regional climate models

Eight atmospheric regional climate models (RCMs) were run for the period September 1997 to October 1998 over the western Arctic Ocean. This period was coincident with the observational campaign of the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The RCMs shared common domains, centred on the SHEBA observation camp, along with a common model horizontal resolution, but differed in their vertical structure and physical parameterizations. All RCMs used the same lateral and surface boundary conditions. Surface downwelling solar and terrestrial radiation, surface albedo, vertically integrated water vapour, liquid water path and cloud cover from each model are evaluated against the SHEBA observation data. Downwelling surface radiation, vertically integrated water vapour and liquid water path are reasonably well simulated at monthly and daily timescales in the model ensemble mean, but with considerable differences among individual models. Simulated surface albedos are relatively accurate in the winter season, but become increasingly inaccurate and variable in the melt season, thereby compromising the net surface radiation budget. Simulated cloud cover is more or less uncorrelated with observed values at the daily timescale. Even for monthly averages, many models do not reproduce the annual cycle correctly. The inter-model spread of simulated cloud-cover is very large, with no model appearing systematically superior. Analysis of the co-variability of terms controlling the surface radiation budget reveal some of the key processes requiring improved treatment in Arctic RCMs. Improvements in the parameterization of cloud amounts and surface albedo are most urgently needed to improve the overall performance of RCMs in the Arctic.     

Biases in the diurnal temperature range in Central Europe in an ensemble of regional climate models and their possible causes

The study examines how regional climate models (RCMs) reproduce the diurnal temperature range (DTR) in their control simulations over Central Europe. We evaluate 30-year runs driven by perfect boundary conditions (the ERA40 reanalysis, 1961–1990) and a global climate model (ECHAM5) of an ensemble of RCMs with 25-km resolution from the ENSEMBLES project. The RCMs’ performance is compared against the dataset gridded from a high-density stations network. We find that all RCMs underestimate DTR in all seasons, notwithstanding whether driven by ERA40 or ECHAM5. Underestimation is largest in summer and smallest in winter in most RCMs. The relationship of the models’ errors to indices of atmospheric circulation and cloud cover is discussed to reveal possible causes of the biases. In all seasons and all simulations driven by ERA40 and ECHAM5, underestimation of DTR is larger under anticyclonic circulation and becomes smaller or negligible for cyclonic circulation. In summer and transition seasons, underestimation tends to be largest for the southeast to south flow associated with warm advection, while in winter it does not depend on flow direction. We show that the biases in DTR, which seem common to all examined RCMs, are also related to cloud cover simulation. However, there is no general tendency to overestimate total cloud amount under anticyclonic conditions in the RCMs, which suggests the large negative bias in DTR for anticyclonic circulation cannot be explained by a bias in cloudiness. Errors in simulating heat and moisture fluxes between land surface and atmosphere probably contribute to the biases in DTR as well.     

An evaluation of the surface radiation budget over North America for a suite of regional climate models against surface station observations

Components of the surface radiation budget (SRB) [incoming shortwave radiation (ISR) and downwelling longwave radiation (DLR)] and cloud cover are assessed for three regional climate models (RCM) forced by analysed boundary conditions, over North America. We present a comparison of the mean seasonal and diurnal cycles of surface radiation between the three RCMs, and surface observations. This aids in identifying in what type of sky situation simulated surface radiation budget errors arise. We present results for total-sky conditions as well as overcast and clear-sky conditions separately. Through the analysis of normalised frequency distributions we show the impact of varying cloud cover on the simulated and observed surface radiation budget, from which we derive observed and model estimates of surface cloud radiative forcing. Surface observations are from the NOAA SURFRAD network. For all models DLR all-sky biases are significantly influenced by cloud-free radiation, cloud emissivity and cloud cover errors. Simulated cloud-free DLR exhibits a systematic negative bias during cold, dry conditions, probably due to a combination of omission of trace gas contributions to the DLR and a poor treatment of the water vapor continuum at low water vapor concentrations. Overall, models overestimate ISR all-sky in summer, which is primarily linked to an underestimate of cloud cover. Cloud-free ISR is relatively well simulated by all RCMs. We show that cloud cover and cloud-free ISR biases can often compensate to result in an accurate total-sky ISR, emphasizing the need to evaluate the individual components making up the total simulated SRB.     

2015年12月29日北极地面爆发性增温的成因分析

利用2015年NCEP/NCAR再分析一日四时次资料和日资料,应用区域平均、热流量方程估算等方法对2015年12月29日北极爆发性增温的原因进行研究。结果表明,2015年12月29日北极出现爆发性增温,日增温幅度最高达到25℃以上。增温期间,受到强盛温带气旋系统和反气旋系统的共同作用,增温区域出现强盛的南风,风速最大值达到20 m s-1以上,位置不断北进达到北极点。强盛的南风为北极地区带来强盛的暖平流,同时暖湿空气进入北极后,增温区上空云量明显增加。12月28日至12月29日温度平流由冷平流转变为暖平流,暖平流的中心区域与温度爆发性增长的区域有很好的对应关系,暖平流是北极爆发性增温的重要原因。对于一直处于极夜的北极地区,由于云量的增加,大气顶向上长波辐射减少,加剧了温度的上升。温度平流增温贡献率为20.4%,垂直项的贡献率为－9.9%,非绝热作用贡献率为89.5%,温度平流和非绝热作用共同导致了本次北极地区的爆发性增温,非绝热作用是本次爆发性增温最重要的增温因素。     

A sensitivity experiment for the removal of Arctic sea ice with the French spectral general circulation model

Sea ice has a major influence on climate in high latitudes. In this paper we analyzed the impact of removal of Arctic sea-ice cover on the climate simulated by a T42 20-level version of the French spectral model Emeraude. The control experiment was the second winter of an annual cycle simulation of the present climate. In the perturbed simulation the Arctic sea-ice cover was replaced by open ocean maintained at the freezing temperature of sea water. The zonal mean patterns of the model response were found to be in good agreement with earlier simulations of Fletcher et al. and Warshaw and Rapp. The atmospheric warming, caused by the increase of upward fluxes of sensible and latent heat and of longwave radiation from the ice-free ocean surface, is largely limited to the high latitudes poleward of 70° N and the lower half of the troposphere and leads to a surface pressure decrease and a precipitation increase over this area. We also analyze the geographical distribution of the response and the mechanisms that can explain the simulated cooling over Eurasia in relation to the energy budget at the surface. Finally, we discuss the reduction of cloud cover over the ice-free Arctic, which was an unexpected result of our simulation, and conclude that further studies are necessary to resolve the question of cumulus convection and cloud process parameterization in high latitudes.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     

The radiation budget in a regional climate model

The long- and short-wave components of the radiation budget are among the most important quantities in climate modelling. In this study, we evaluated the radiation budget at the earth??s surface and at the top of atmosphere over Europe as simulated by the regional climate model CLM. This was done by comparisons with radiation budgets as computed by the GEWEX/SRB satellite-based product and as realised in the ECMWF re-analysis ERA40. Our comparisons show that CLM has a tendency to underestimate solar radiation at the surface and the energy loss by thermal emission. We found a clear statistical dependence of radiation budget imprecision on cloud cover and surface albedo uncertainties in the solar spectrum. In contrast to cloud fraction errors, surface temperature errors have a minor impact on radiation budget uncertainties in the long-wave spectrum. We also evaluated the impact of the number of atmospheric layers used in CLM simulations. CLM simulations with 32 layers perform better than do those with 20 layers in terms of the surface radiation budget components but not in terms of the outgoing long-wave radiation and of radiation divergence. Application of the evaluation approach to similar simulations with two additional regional climate models confirmed the results and showed the usefulness of the approach.     

Seasonal climatology of cloud at resolute (75°N)

Abstract

An analysis of surface observations of cloud characteristics from a selected high‐latitude station, Resolute (N.W.T., Canada), is described. The data set has a high temporal resolution (1 h) and is extensive although here we report only on an analysis of 10 years: 1970–1979, inclusive. The pattern of cloudiness variations is more complex than previous studies of Arctic data have suggested. The predominant reported low‐level cloud type is stratocumulus, not stratus. The generally overcast summer conditions are found to extend over a considerable period when cloud cover is composed of several layers, often of types other than stratus. This observation of multilayering suggests that middle and high cloud layers may occur more frequently than they can be observed. Clearly a more accurate awareness of hidden cloud is important for improving solutions of the planetary radiation budget. The surface radiation budget is found to be strongly affected by the development of the summertime overcast but also exhibits features caused by the mid‐summer break‐up of the lower cloud layer.     

The surface radiation budget over South America in a set of regional climate models from the CLARIS-LPB project

The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990–2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA.     

Distributions of Downwelling Radiance at 10 and 20 μm in the High Arctic

In the Arctic, most of the infrared (IR) energy emitted by the surface escapes to space in two atmospheric windows centred at 10 and 20?μm. As the Arctic warms and its water vapour burden increases, the 20?μm cooling-to-space window, in particular, is expected to become increasingly opaque (or “closed”), trapping more IR radiation, with implications for the Arctic’s radiative energy balance. Since 2006, the Canadian Network for the Detection of Atmospheric Change has measured downwelling IR radiation with Atmospheric Emitted Radiance Interferometers at the Polar Environment Atmospheric Research Laboratory at Eureka, Canada, providing measurements of the 10 and 20?μm windows in the High Arctic. In this work, measurements of the distribution of downwelling 10 and 20?µm brightness temperatures at Eureka are separated based on cloud cover, providing a comparison to an existing 10?µm climatology from the Southern Great Plains. The downwelling radiance at both 10 and 20?μm exhibits strong seasonal variability as a result of changes in cloud cover, temperature, and water vapour. Given the 20?µm window’s limited transparency, its ability to allow surface IR radiation to escape to space is found to be highly sensitive to changes in atmospheric water vapour and temperature. When separated by season, brightness temperatures in the 20?µm window are independent of cloud optical thickness in the summer, indicating that this window is opaque in the summer. This may have long-term consequences, particularly as warmer temperatures and increased water vapour “close” the 20?μm window for a prolonged period each year.     

The WAMME regional model intercomparison study

Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed.     

Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs.     

High resolution regional climate model simulations for Germany: part I—validation

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.     

Polar amplification of climate change in coupled models

The Northern Hemisphere polar amplification of climate change is documented in models taking part in the Coupled Model Intercomparison Project and in the new version of the Community Climate System Model. In particular, the magnitude, spatial distribution, and seasonality of the surface warming in the Arctic is examined and compared among the models. The range of simulated polar warming in the Arctic is from 1.5 to 4.5 times the global mean warming. While ice-albedo feedback is likely to account for much of the polar amplification, the strength of the feedback depends on numerous physical processes and parametrizations which differ considerably among the models. Nonetheless, the mean sea-ice state in the control (or present) climate is found to influence both the magnitude and spatial distribution of the high-latitude warming in the models. In particular, the latitude of the maximum warming is correlated inversely and significantly with sea-ice extent in the control climate. Additionally, models with relatively thin Arctic ice cover in the control climate tend to have higher polar amplification. An intercomparison of model results also shows that increases in poleward ocean heat transport at high latitudes and increases in polar cloud cover are significantly correlated to amplified Arctic warming. This suggests that these changes in the climate state may modify polar amplification. No significant correlation is found between polar amplification and the control climate continental ice and snow cover.     

Cloud type and cloud cover effects on the surface radiative balance at several Polar sites

Summary ?The present work concerns measurements performed at five Polar sites in order to study the influence of cloud type and cloud cover on the surface radiative balance. Cloud cover index was retrieved with the Kasten and Czeplak formula (1980), and comparison with observed values showed the possibility of applying this formula in Polar regions. The Duchon and O’Malley (1999) methodology was adopted to estimate the cloud types present during the measurement period for each site. The results show that during the Antarctic summer clouds have a warming effect on the surface, while during a melting event recorded in the Arctic site clouds have a net cooling effect on the surface. This result allows us to conclude that, during a melting period a different cloud type formation, and a lower surface albedo, modify the effects of clouds on the surface radiation balance. Received April 5, 2002; revised August 1, 2002; accepted August 17, 2002     

Twentieth century simulation of the southern hemisphere climate in coupled models. Part II: sea ice conditions and variability

We examine the representation of the mean state and interannual variability of Antarctic sea ice in six simulations of the twentieth century from coupled models participating in the Intergovernmental Panel on Climate Change fourth assessment report. The simulations exhibit a largely seasonal southern hemisphere ice cover, as observed. There is a considerable scatter in the monthly simulated climatological ice extent among different models, but no consistent bias when compared to observations. The scatter in maximum winter ice extent among different models is correlated to the strength of the climatological zonal winds suggesting that wind forced ice transport is responsible for much of this scatter. Observations show that the leading mode of southern hemisphere ice variability exhibits a dipole structure with anomalies of one sign in the Atlantic sector associated with anomalies of the opposite sign in the Pacific sector. The observed ice anomalies also exhibit eastward propagation with the Antarctic circumpolar current, as part of the documented Antarctic circumpolar wave phenomenon. Many of the models do simulate dipole-like behavior in sea ice anomalies as the leading mode of ice variability, but there is a large discrepancy in the eastward propagation of these anomalies among the different models. Consistent with observations, the simulated Antarctic dipole-like variations in the ice cover are led by sea-level pressure anomalies in the Amundsen/ Bellingshausen Sea. These are associated, to different degrees in different models, with both the southern annular mode and the El Nino-Southern Oscillation (ENSO). There are indications that the magnitude of the influence of ENSO on the southern hemisphere ice cover is related to the strength of ENSO events simulated by the different models.     

不同区域气候模式对中国地区温度和降水的长期模拟比较

利用亚洲区域模式比较计划RMIP第二阶段五个区域模式和一个变网格全球模式，对中国地区1988年12月～1998年11月十年模拟的平均温度和降水结果，分析比较了不同区域气候模式对中国地区温度和降水的模拟能力。研究结果表明:几乎所有模式都能模拟出中国地区多年平均温度和降水的基本空间分布形态，但模式模拟的温度普遍偏低，在大部分区域，大多数模式模拟的降水偏多，而且不同模式之间存在较大差别。模式能较好地反映出中国地区温度的年际变化，对夏季降水的年际变化模拟较差，对冬季模拟较好。     

The 20th century cooling trend over the southeastern United States

Portions of the southern and southeastern United States, primarily Mississippi, Alabama, and Georgia, have experienced century-long (1895–2007) downward air temperature trends that occur in all seasons. Superimposed on them are shifts in mean temperatures on decadal scales characterized by alternating warm (1930s–1940s, 1990s) and cold (1900s; 1960s–1970s) regimes. Regional atmospheric circulation and SST teleconnection indices, station-based cloud cover and soil moisture (Palmer drought severity index) data are used in stepwise multiple linear regression models. These models identify predictors linked to observed winter, summer, and annual Southeastern air temperature variability, the observed variance (r²) they explain, and the resulting prediction and residual time series. Long-term variations and trends in tropical Pacific sea temperatures, cloud cover, soil moisture and the North Atlantic and Arctic oscillations account for much of the air temperature downtrends. Soil moisture and cloud cover are the primary predictors of 59.6 % of the observed summer temperature variance. While the teleconnections, cloud cover and moisture data account for some of the annual and summer Southeastern cooling trend, large significant downward trending residuals remain in winter and summer. Comparison is made to the northeastern United States where large twentieth century upward air temperature trends are driven by cloud cover increases and Atlantic Multidecadal Oscillation (AMO) variability. Differences between the Northeastern warming and the Southeastern cooling trends in summer are attributable in part to the differing roles of cloud cover, soil moisture, the Arctic Oscillation and the AMO on air temperatures of the 2 regions.     

Dynamical Downscaling of the Arctic Climate with a Focus on Polar Cyclone Climatology

We present a dynamical downscaling of the Arctic climatology using a high-resolution implementation of the Polar Weather Research and Forecasting, version 3.6 (WRF3.6) model, with a focus on Arctic cyclone activity. The study period is 1979–2004 and the driving fields are data from the Hadley Centre Global Environmental Model, version 2, with an Earth System component (HadGEM2-ES) simulations. We show that the results from the Polar WRF model provide significantly improved simulations of the frequency, intensity, and size of cyclones compared with the HadGEM2-ES simulations. Polar WRF reproduces the intensity of winter cyclones found in ERA-Interim, the global atmospheric reanalysis produced by the European Centre for Medium-range Weather Forecasts (ECMWF), and suggests that the average minimum central pressure of the cyclones is about 10?hPa lower than that derived from HadGEM2-ES simulations. Although both models underestimate the frequency of summer Arctic cyclones, Polar WRF simulations suggest there are 10.5% more cyclones per month than do HadGEM2-ES results. Overall, the Polar WRF model captures more intense and smaller cyclones than are obtained in HadGEM2-ES results, in better agreement with the ERA-Interim reanalysis data. Our results also show that the improved simulations of Arctic synoptic weather systems contribute to better simulations of atmospheric surface fields. The Polar WRF model is better able to simulate both the spatial patterns and magnitudes of the ERA-Interim reanalysis data than HadGEM2-ES is; in particular, the latter overestimates the absorbed solar radiation in the Arctic basin by as much as 30?W?m^?2 and underestimates longwave radiation by about 10?W?m^?2 in summer. Our results suggest that the improved simulations of longwave and solar radiation are partly associated with a better simulation of cloud liquid water content in the Polar WRF model, which is linked to improvements in the simulation of cyclone frequency and intensity and the resulting transient eddy transports of heat and water vapour.     

The simulated atmospheric response to expansion of the Arctic boreal forest biome

Over the last century, the Arctic has warmed at twice the rate of the planet as a whole. Observational evidence indicates that this rapid warming is affecting the tundra and boreal forest biomes by changing their structure and geographic distribution. A global climate model (GCM) was used to explore the atmospheric response to boreal forest expansion by applying a one-grid cell shift of the forest into tundra. This subtle shift is meant to represent the expansion that would occur this century rather than more extreme scenarios predicted by dynamic vegetation models. Results show that this shift causes an average annual warming of 0.3 °C over the region because of a reduction in the surface albedo and an increase in net radiation. A warming of ~1.0 °C occurs in spring when the forest masks the higher albedo snow-covered surface and results in snowmelt and a reduction in cloud cover. Results fail to show a larger-scale dynamical response although some warming of the lower and mid troposphere occurs in July. No changes were found in the position or strength of the Arctic frontal zone as some studies have indicated will occur with a shift in the boreal forest-tundra boundary. These findings suggest that coupled model simulations that predict larger changes in vegetation distribution are likely overemphasizing the amount of Arctic warming that will occur this century. These findings also indicate that a realistic dynamical response to subtle land cover change might not be correctly simulated by GCMs run at coarse spatial resolutions.     

气候模式分辨率对气溶胶气候效应模拟结果的影响

气候模式分辨率作为影响模式模拟结果的重要因素,其对气溶胶与云相互作用的影响尚未全面认识。利用公共大气模型CAM5.3在3种分辨率（2°、1°、0.5°）下,分别采用2000年和1850年气溶胶排放情景进行试验,检验提高分辨率是否能改进气候模式的模拟能力,分析不同分辨率下气溶胶气候效应的异同,探索模式分辨率对气溶胶气候效应数值模拟结果的影响。通过观测资料与模式结果对比发现,提高分辨率可以明显改进模式对总云量、云短波辐射强迫的模拟能力,0.5°分辨率下模拟结果与观测更接近,其他变量并无明显改善。在不同分辨率下,全球平均的气溶胶气候效应较为一致,总云量、云水路径均增加,云短波和长波辐射强迫均加强,而云顶的云滴有效半径和降水均减小,地面气温降低。不同分辨率下,气溶胶增加引起的气溶胶光学厚度、云水路径、地面温度、云短波和长波辐射强迫变化的纬向平均分布相似但大小存在差异;而降水和云量变化的纬向分布与大小均存在较大差异,在区域尺度上还存在较大的不确定性。全球平均而言, 0.5°分辨率下气溶胶的间接辐射强迫相比1°分辨率下的结果降低了2.5%,相比2°分辨率下的结果降低了6.4%。提高模式分辨率可以部分改进模式模拟能力,同时,气溶胶的间接效应随着模式分辨率的提高而减弱。但气溶胶引起的云量、降水的变化在不同分辨率下差异较大,存在较大的不确定性。